Upload folder using huggingface_hub

.gitattributes

@@ -319,3 +319,4 @@ runs/slm_decoder_models/phi-4/phi-4-phi4_ordinal_corn_lora-C5/logs/events.out.tf
 runs/slm_decoder_models/phi-4/phi-4-phi4_ordinal_corn_lora-C5/results/checkpoint-416/optimizer.pt filter=lfs diff=lfs merge=lfs -text
 runs/slm_decoder_models/phi-4/phi-4-phi4_ordinal_corn_lora-C5/results/checkpoint-416/rng_state.pth filter=lfs diff=lfs merge=lfs -text
 runs/slm_decoder_models/phi-4/phi-4-phi4_ordinal_corn_lora-C5/results/checkpoint-416/scheduler.pt filter=lfs diff=lfs merge=lfs -text
+runs/slm_decoder_models/llama/Llama-3.1-8B-llama31_ordinal_corn_lora-C4/results/checkpoint-224/optimizer.pt filter=lfs diff=lfs merge=lfs -text

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C1/emissions.csv

@@ -1,2 +1,3 @@
-timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
-2025-06-02T12:32:32,jbcs2025,827d2eee-877f-4316-9a2c-18ea0895a0a2,bert-base-portuguese-cased-encoder_ordinal_coral-C1,71.40745383827016,0.0003707009287543563,5.191347805145835e-06,83.04545454545455,213.74904943841295,70.0,0.0014833025213244404,0.003772676629239413,0.0013590733798945118,0.0066150525304583645,France,FRA,île-de-france,,,Linux-5.15.0-136-generic-x86_64-with-glibc2.35,3.12.10,3.0.2,192,INTEL(R) XEON(R) PLATINUM 8568Y+,1,1 x NVIDIA H200,2.3494,48.8558,2015.3635139465332,machine,N,1.0
+version https://git-lfs.github.com/spec/v1
+oid sha256:4998022454fd36c0fcb87fa8bb0e2ba95f8a829b14ca9a3a24c425601ff13872
+size 861

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C1/evaluation_results.csv

@@ -1,4 +1,3 @@
-eval_loss,eval_model_preparation_time,eval_accuracy,eval_RMSE,eval_QWK,eval_HDIV,eval_Macro_F1,eval_Micro_F1,eval_Weighted_F1,eval_TP_0,eval_TN_0,eval_FP_0,eval_FN_0,eval_TP_1,eval_TN_1,eval_FP_1,eval_FN_1,eval_TP_2,eval_TN_2,eval_FP_2,eval_FN_2,eval_TP_3,eval_TN_3,eval_FP_3,eval_FN_3,eval_TP_4,eval_TN_4,eval_FP_4,eval_FN_4,eval_TP_5,eval_TN_5,eval_FP_5,eval_FN_5,eval_runtime,eval_samples_per_second,eval_steps_per_second,epoch,reference,timestamp,id
-45.5702018737793,0.0016,0.08333333333333333,80.45326141759122,0.010583644479379983,0.24242424242424243,0.048893916540975364,0.08333333333333333,0.06528520499108734,0,131,0,1,0,100,32,0,3,67,58,4,8,62,31,31,0,69,0,63,0,110,0,22,0.4696,281.103,19.166,-1,validation_before_training,2025-06-02 12:31:40,bert-base-portuguese-cased-encoder_ordinal_coral-C1
-9.964560508728027,0.0016,0.6666666666666666,25.34608929251695,0.6442229454841335,0.0,0.43042272064701176,0.6666666666666666,0.6472184106547204,0,131,0,1,0,132,0,0,1,124,1,6,27,78,15,12,51,44,25,12,9,107,3,13,0.2354,560.736,38.232,13.0,validation_after_training,2025-06-02 12:31:40,bert-base-portuguese-cased-encoder_ordinal_coral-C1
-9.004440307617188,0.0016,0.717391304347826,24.07717061715384,0.6294307196562836,0.007246376811594235,0.39602986385595085,0.717391304347826,0.685388223762515,0,137,0,1,0,138,0,0,4,124,4,6,52,58,14,14,43,66,21,8,0,128,0,10,0.2239,616.403,40.2,13.0,test_results,2025-06-02 12:31:40,bert-base-portuguese-cased-encoder_ordinal_coral-C1
+version https://git-lfs.github.com/spec/v1
+oid sha256:ed4727a808448dab20f50354dcb74162ec3bbc2c844a0060f52d26b7d4f6f37d
+size 1473

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C1/results/best_model/config.json

@@ -1,45 +1,3 @@
-{
-  "architectures": [
-    "BertForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cf1f6d6785c3b5bcfc91fad895c1ed8a279abdc99a665ea0767faf219a6e2d9
+size 1047

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C1/results/best_model/special_tokens_map.json

@@ -1,7 +1,3 @@
-{
-  "cls_token": "[CLS]",
-  "mask_token": "[MASK]",
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "unk_token": "[UNK]"
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6d346be366a7d1d48332dbc9fdf3bf8960b5d879522b7799ddba59e76237ee3
+size 125

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C1/results/best_model/tokenizer_config.json

@@ -1,58 +1,3 @@
-{
-  "added_tokens_decoder": {
-    "0": {
-      "content": "[PAD]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "100": {
-      "content": "[UNK]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "101": {
-      "content": "[CLS]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "102": {
-      "content": "[SEP]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "103": {
-      "content": "[MASK]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    }
-  },
-  "clean_up_tokenization_spaces": true,
-  "cls_token": "[CLS]",
-  "do_basic_tokenize": true,
-  "do_lower_case": false,
-  "extra_special_tokens": {},
-  "mask_token": "[MASK]",
-  "model_max_length": 1000000000000000019884624838656,
-  "never_split": null,
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "strip_accents": null,
-  "tokenize_chinese_chars": true,
-  "tokenizer_class": "BertTokenizer",
-  "unk_token": "[UNK]"
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ab044e4a71cdb2a5cff548e16d3bcd46a757848ef861743426c44a134b00da1
+size 1301

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C1/results/checkpoint-256/config.json

@@ -1,45 +1,3 @@
-{
-  "architectures": [
-    "BertForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cf1f6d6785c3b5bcfc91fad895c1ed8a279abdc99a665ea0767faf219a6e2d9
+size 1047

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C1/results/checkpoint-256/trainer_state.json

@@ -1,377 +1,3 @@
-{
-  "best_global_step": 256,
-  "best_metric": 0.6442229454841335,
-  "best_model_checkpoint": "/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-256",
-  "epoch": 8.0,
-  "eval_steps": 500,
-  "global_step": 256,
-  "is_hyper_param_search": false,
-  "is_local_process_zero": true,
-  "is_world_process_zero": true,
-  "log_history": [
-    {
-      "epoch": 1.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 7,
-      "eval_FN_3": 39,
-      "eval_FN_4": 0,
-      "eval_FN_5": 22,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 0,
-      "eval_FP_4": 69,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.12923076923076923,
-      "eval_Micro_F1": 0.4772727272727273,
-      "eval_QWK": 0.0,
-      "eval_RMSE": 35.67530340063379,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 125,
-      "eval_TN_3": 93,
-      "eval_TN_4": 0,
-      "eval_TN_5": 110,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 0,
-      "eval_TP_4": 63,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.30839160839160845,
-      "eval_accuracy": 0.4772727272727273,
-      "eval_loss": 19.501850128173828,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2312,
-      "eval_samples_per_second": 570.847,
-      "eval_steps_per_second": 38.921,
-      "step": 32
-    },
-    {
-      "epoch": 2.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 1,
-      "eval_FN_3": 17,
-      "eval_FN_4": 25,
-      "eval_FN_5": 22,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 14,
-      "eval_FP_3": 24,
-      "eval_FP_4": 28,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.0,
-      "eval_Macro_F1": 0.31024775801793586,
-      "eval_Micro_F1": 0.5,
-      "eval_QWK": 0.5307289964040536,
-      "eval_RMSE": 32.47376563543955,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 111,
-      "eval_TN_3": 69,
-      "eval_TN_4": 41,
-      "eval_TN_5": 110,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 6,
-      "eval_TP_3": 22,
-      "eval_TP_4": 38,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.4576941323863349,
-      "eval_accuracy": 0.5,
-      "eval_loss": 14.802102088928223,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.228,
-      "eval_samples_per_second": 578.823,
-      "eval_steps_per_second": 39.465,
-      "step": 64
-    },
-    {
-      "epoch": 3.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 7,
-      "eval_FN_3": 6,
-      "eval_FN_4": 25,
-      "eval_FN_5": 22,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 35,
-      "eval_FP_4": 26,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.24304952535138719,
-      "eval_Micro_F1": 0.5378787878787878,
-      "eval_QWK": 0.45231245850851953,
-      "eval_RMSE": 30.15113445777636,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 125,
-      "eval_TN_3": 58,
-      "eval_TN_4": 43,
-      "eval_TN_5": 110,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 33,
-      "eval_TP_4": 38,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.4678550164237117,
-      "eval_accuracy": 0.5378787878787878,
-      "eval_loss": 12.265461921691895,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2151,
-      "eval_samples_per_second": 613.724,
-      "eval_steps_per_second": 41.845,
-      "step": 96
-    },
-    {
-      "epoch": 3.125,
-      "grad_norm": 27.78256607055664,
-      "learning_rate": 4.696180555555556e-05,
-      "loss": 20.0208,
-      "step": 100
-    },
-    {
-      "epoch": 4.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 7,
-      "eval_FN_3": 13,
-      "eval_FN_4": 18,
-      "eval_FN_5": 22,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 26,
-      "eval_FP_4": 35,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.24015984015984015,
-      "eval_Micro_F1": 0.5378787878787878,
-      "eval_QWK": 0.42051041910559595,
-      "eval_RMSE": 30.15113445777636,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 125,
-      "eval_TN_3": 67,
-      "eval_TN_4": 34,
-      "eval_TN_5": 110,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 26,
-      "eval_TP_4": 45,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.46921260557624195,
-      "eval_accuracy": 0.5378787878787878,
-      "eval_loss": 10.788846969604492,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2155,
-      "eval_samples_per_second": 612.391,
-      "eval_steps_per_second": 41.754,
-      "step": 128
-    },
-    {
-      "epoch": 5.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 7,
-      "eval_FN_3": 14,
-      "eval_FN_4": 14,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 17,
-      "eval_FP_4": 29,
-      "eval_FP_5": 5,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.3448168234985089,
-      "eval_Micro_F1": 0.6136363636363636,
-      "eval_QWK": 0.54574332909784,
-      "eval_RMSE": 28.06917861068948,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 125,
-      "eval_TN_3": 76,
-      "eval_TN_4": 40,
-      "eval_TN_5": 105,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 25,
-      "eval_TP_4": 49,
-      "eval_TP_5": 7,
-      "eval_Weighted_F1": 0.5827282700457503,
-      "eval_accuracy": 0.6136363636363636,
-      "eval_loss": 10.468523979187012,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2244,
-      "eval_samples_per_second": 588.159,
-      "eval_steps_per_second": 40.102,
-      "step": 160
-    },
-    {
-      "epoch": 6.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 7,
-      "eval_FN_3": 15,
-      "eval_FN_4": 8,
-      "eval_FN_5": 22,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 16,
-      "eval_FP_4": 37,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.2634544712127399,
-      "eval_Micro_F1": 0.5984848484848485,
-      "eval_QWK": 0.45875152998776003,
-      "eval_RMSE": 28.4977404739606,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 125,
-      "eval_TN_3": 77,
-      "eval_TN_4": 32,
-      "eval_TN_5": 110,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 24,
-      "eval_TP_4": 55,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.5182263632651547,
-      "eval_accuracy": 0.5984848484848485,
-      "eval_loss": 10.83399772644043,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2168,
-      "eval_samples_per_second": 608.989,
-      "eval_steps_per_second": 41.522,
-      "step": 192
-    },
-    {
-      "epoch": 6.25,
-      "grad_norm": 96.18888092041016,
-      "learning_rate": 3.828125e-05,
-      "loss": 8.3446,
-      "step": 200
-    },
-    {
-      "epoch": 7.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 7,
-      "eval_FN_3": 17,
-      "eval_FN_4": 7,
-      "eval_FN_5": 21,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 14,
-      "eval_FP_4": 38,
-      "eval_FP_5": 1,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.27667515923566877,
-      "eval_Micro_F1": 0.5984848484848485,
-      "eval_QWK": 0.46387002909796315,
-      "eval_RMSE": 28.4977404739606,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 125,
-      "eval_TN_3": 79,
-      "eval_TN_4": 31,
-      "eval_TN_5": 109,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 22,
-      "eval_TP_4": 56,
-      "eval_TP_5": 1,
-      "eval_Weighted_F1": 0.5276970340346135,
-      "eval_accuracy": 0.5984848484848485,
-      "eval_loss": 10.23282241821289,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2231,
-      "eval_samples_per_second": 591.587,
-      "eval_steps_per_second": 40.335,
-      "step": 224
-    },
-    {
-      "epoch": 8.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 6,
-      "eval_FN_3": 12,
-      "eval_FN_4": 12,
-      "eval_FN_5": 13,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 1,
-      "eval_FP_3": 15,
-      "eval_FP_4": 25,
-      "eval_FP_5": 3,
-      "eval_HDIV": 0.0,
-      "eval_Macro_F1": 0.43042272064701176,
-      "eval_Micro_F1": 0.6666666666666666,
-      "eval_QWK": 0.6442229454841335,
-      "eval_RMSE": 25.34608929251695,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 124,
-      "eval_TN_3": 78,
-      "eval_TN_4": 44,
-      "eval_TN_5": 107,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 1,
-      "eval_TP_3": 27,
-      "eval_TP_4": 51,
-      "eval_TP_5": 9,
-      "eval_Weighted_F1": 0.6472184106547204,
-      "eval_accuracy": 0.6666666666666666,
-      "eval_loss": 9.964560508728027,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2152,
-      "eval_samples_per_second": 613.402,
-      "eval_steps_per_second": 41.823,
-      "step": 256
-    }
-  ],
-  "logging_steps": 100,
-  "max_steps": 640,
-  "num_input_tokens_seen": 0,
-  "num_train_epochs": 20,
-  "save_steps": 500,
-  "stateful_callbacks": {
-    "EarlyStoppingCallback": {
-      "args": {
-        "early_stopping_patience": 5,
-        "early_stopping_threshold": 0.0
-      },
-      "attributes": {
-        "early_stopping_patience_counter": 0
-      }
-    },
-    "TrainerControl": {
-      "args": {
-        "should_epoch_stop": false,
-        "should_evaluate": false,
-        "should_log": false,
-        "should_save": true,
-        "should_training_stop": false
-      },
-      "attributes": {}
-    }
-  },
-  "total_flos": 1052472569856000.0,
-  "train_batch_size": 16,
-  "trial_name": null,
-  "trial_params": null
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:d0a5a65ec5317435b4c966963a2acd77477d69ef7fb6af0f499ad66d3b1a9a24
+size 9959

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C1/run_experiment.log

@@ -1,370 +1,3 @@
-[2025-06-02 12:31:17,530][__main__][INFO] - cache_dir: /tmp/
-dataset:
-  name: kamel-usp/aes_enem_dataset
-  split: JBCS2025
-training_params:
-  seed: 42
-  num_train_epochs: 20
-  logging_steps: 100
-  metric_for_best_model: QWK
-  bf16: true
-post_training_results:
-  model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
-experiments:
-  model:
-    name: neuralmind/bert-base-portuguese-cased
-    type: encoder_ordinal_coral
-    num_labels: 6
-    output_dir: ./results/
-    logging_dir: ./logs/
-    best_model_dir: ./results/best_model
-  tokenizer:
-    name: neuralmind/bert-base-portuguese-cased
-  dataset:
-    grade_index: 0
-  training_params:
-    weight_decay: 0.01
-    warmup_ratio: 0.1
-    learning_rate: 5.0e-05
-    train_batch_size: 16
-    eval_batch_size: 16
-    gradient_accumulation_steps: 1
-    gradient_checkpointing: false
-
-[2025-06-02 12:31:21,434][__main__][INFO] - GPU 0: NVIDIA H200 | TDP ≈ 700 W
-[2025-06-02 12:31:21,435][__main__][INFO] - Starting the Fine Tuning training process.
-[2025-06-02 12:31:25,899][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-02 12:31:25,900][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-02 12:31:27,515][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
-[2025-06-02 12:31:27,515][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
-[2025-06-02 12:31:27,515][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
-[2025-06-02 12:31:27,515][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
-[2025-06-02 12:31:27,515][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
-[2025-06-02 12:31:27,515][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
-[2025-06-02 12:31:27,515][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-02 12:31:27,516][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-02 12:31:27,540][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-02 12:31:27,541][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-02 12:31:27,555][__main__][INFO] - Tokenizer function parameters- Padding:max_length; Truncation: True
-[2025-06-02 12:31:28,129][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-02 12:31:28,130][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-02 12:31:39,897][transformers.modeling_utils][INFO] - loading weights file pytorch_model.bin from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/pytorch_model.bin
-[2025-06-02 12:31:39,994][transformers.modeling_utils][INFO] - Since the `torch_dtype` attribute can't be found in model's config object, will use torch_dtype={torch_dtype} as derived from model's weights
-[2025-06-02 12:31:39,994][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
-[2025-06-02 12:31:40,143][transformers.safetensors_conversion][INFO] - Attempting to create safetensors variant
-[2025-06-02 12:31:40,626][transformers.modeling_utils][INFO] - Some weights of the model checkpoint at neuralmind/bert-base-portuguese-cased were not used when initializing BertForSequenceClassification: ['cls.predictions.bias', 'cls.predictions.decoder.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.dense.weight', 'cls.seq_relationship.bias', 'cls.seq_relationship.weight']
-- This IS expected if you are initializing BertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
-- This IS NOT expected if you are initializing BertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
-[2025-06-02 12:31:40,627][transformers.modeling_utils][WARNING] - Some weights of BertForSequenceClassification were not initialized from the model checkpoint at neuralmind/bert-base-portuguese-cased and are newly initialized: ['classifier.bias', 'classifier.weight']
-You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
-[2025-06-02 12:31:40,630][transformers.training_args][INFO] - PyTorch: setting up devices
-[2025-06-02 12:31:40,667][__main__][INFO] - Total steps: 620. Number of warmup steps: 62
-[2025-06-02 12:31:40,673][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
-[2025-06-02 12:31:40,691][transformers.trainer][INFO] - Using auto half precision backend
-[2025-06-02 12:31:40,693][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:31:40,696][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:31:40,696][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:31:40,696][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:31:40,804][transformers.safetensors_conversion][INFO] - Safetensors PR exists
-[2025-06-02 12:31:41,165][transformers][INFO] - {'accuracy': 0.08333333333333333, 'RMSE': 80.45326141759122, 'QWK': 0.010583644479379983, 'HDIV': 0.24242424242424243, 'Macro_F1': 0.048893916540975364, 'Micro_F1': 0.08333333333333333, 'Weighted_F1': 0.06528520499108734, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(100), 'FP_1': np.int64(32), 'FN_1': np.int64(0), 'TP_2': np.int64(3), 'TN_2': np.int64(67), 'FP_2': np.int64(58), 'FN_2': np.int64(4), 'TP_3': np.int64(8), 'TN_3': np.int64(62), 'FP_3': np.int64(31), 'FN_3': np.int64(31), 'TP_4': np.int64(0), 'TN_4': np.int64(69), 'FP_4': np.int64(0), 'FN_4': np.int64(63), 'TP_5': np.int64(0), 'TN_5': np.int64(110), 'FP_5': np.int64(0), 'FN_5': np.int64(22)}
-[2025-06-02 12:31:41,297][transformers.trainer][INFO] - The following columns in the Training set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:31:41,303][transformers.trainer][INFO] - ***** Running training *****
-[2025-06-02 12:31:41,303][transformers.trainer][INFO] -   Num examples = 500
-[2025-06-02 12:31:41,303][transformers.trainer][INFO] -   Num Epochs = 20
-[2025-06-02 12:31:41,303][transformers.trainer][INFO] -   Instantaneous batch size per device = 16
-[2025-06-02 12:31:41,303][transformers.trainer][INFO] -   Total train batch size (w. parallel, distributed & accumulation) = 16
-[2025-06-02 12:31:41,303][transformers.trainer][INFO] -   Gradient Accumulation steps = 1
-[2025-06-02 12:31:41,303][transformers.trainer][INFO] -   Total optimization steps = 640
-[2025-06-02 12:31:41,303][transformers.trainer][INFO] -   Number of trainable parameters = 108,926,981
-[2025-06-02 12:31:43,295][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:31:43,297][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:31:43,297][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:31:43,297][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:31:43,529][transformers][INFO] - {'accuracy': 0.4772727272727273, 'RMSE': 35.67530340063379, 'QWK': 0.0, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.12923076923076923, 'Micro_F1': 0.4772727272727273, 'Weighted_F1': 0.30839160839160845, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(125), 'FP_2': np.int64(0), 'FN_2': np.int64(7), 'TP_3': np.int64(0), 'TN_3': np.int64(93), 'FP_3': np.int64(0), 'FN_3': np.int64(39), 'TP_4': np.int64(63), 'TN_4': np.int64(0), 'FP_4': np.int64(69), 'FN_4': np.int64(0), 'TP_5': np.int64(0), 'TN_5': np.int64(110), 'FP_5': np.int64(0), 'FN_5': np.int64(22)}
-[2025-06-02 12:31:43,532][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-32
-[2025-06-02 12:31:43,533][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-32/config.json
-[2025-06-02 12:31:44,444][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-32/model.safetensors
-[2025-06-02 12:31:47,012][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:31:47,014][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:31:47,014][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:31:47,014][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:31:47,243][transformers][INFO] - {'accuracy': 0.5, 'RMSE': 32.47376563543955, 'QWK': 0.5307289964040536, 'HDIV': 0.0, 'Macro_F1': 0.31024775801793586, 'Micro_F1': 0.5, 'Weighted_F1': 0.4576941323863349, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(6), 'TN_2': np.int64(111), 'FP_2': np.int64(14), 'FN_2': np.int64(1), 'TP_3': np.int64(22), 'TN_3': np.int64(69), 'FP_3': np.int64(24), 'FN_3': np.int64(17), 'TP_4': np.int64(38), 'TN_4': np.int64(41), 'FP_4': np.int64(28), 'FN_4': np.int64(25), 'TP_5': np.int64(0), 'TN_5': np.int64(110), 'FP_5': np.int64(0), 'FN_5': np.int64(22)}
-[2025-06-02 12:31:47,246][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-64
-[2025-06-02 12:31:47,247][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-64/config.json
-[2025-06-02 12:31:48,126][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-64/model.safetensors
-[2025-06-02 12:31:48,830][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-32] due to args.save_total_limit
-[2025-06-02 12:31:50,756][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:31:50,757][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:31:50,758][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:31:50,758][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:31:50,974][transformers][INFO] - {'accuracy': 0.5378787878787878, 'RMSE': 30.15113445777636, 'QWK': 0.45231245850851953, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.24304952535138719, 'Micro_F1': 0.5378787878787878, 'Weighted_F1': 0.4678550164237117, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(125), 'FP_2': np.int64(0), 'FN_2': np.int64(7), 'TP_3': np.int64(33), 'TN_3': np.int64(58), 'FP_3': np.int64(35), 'FN_3': np.int64(6), 'TP_4': np.int64(38), 'TN_4': np.int64(43), 'FP_4': np.int64(26), 'FN_4': np.int64(25), 'TP_5': np.int64(0), 'TN_5': np.int64(110), 'FP_5': np.int64(0), 'FN_5': np.int64(22)}
-[2025-06-02 12:31:50,976][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-96
-[2025-06-02 12:31:50,977][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-96/config.json
-[2025-06-02 12:31:51,881][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-96/model.safetensors
-[2025-06-02 12:31:54,435][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:31:54,437][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:31:54,437][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:31:54,437][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:31:54,654][transformers][INFO] - {'accuracy': 0.5378787878787878, 'RMSE': 30.15113445777636, 'QWK': 0.42051041910559595, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.24015984015984015, 'Micro_F1': 0.5378787878787878, 'Weighted_F1': 0.46921260557624195, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(125), 'FP_2': np.int64(0), 'FN_2': np.int64(7), 'TP_3': np.int64(26), 'TN_3': np.int64(67), 'FP_3': np.int64(26), 'FN_3': np.int64(13), 'TP_4': np.int64(45), 'TN_4': np.int64(34), 'FP_4': np.int64(35), 'FN_4': np.int64(18), 'TP_5': np.int64(0), 'TN_5': np.int64(110), 'FP_5': np.int64(0), 'FN_5': np.int64(22)}
-[2025-06-02 12:31:54,656][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-128
-[2025-06-02 12:31:54,657][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-128/config.json
-[2025-06-02 12:31:55,596][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-128/model.safetensors
-[2025-06-02 12:31:56,268][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-96] due to args.save_total_limit
-[2025-06-02 12:31:58,196][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:31:58,199][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:31:58,199][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:31:58,199][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:31:58,424][transformers][INFO] - {'accuracy': 0.6136363636363636, 'RMSE': 28.06917861068948, 'QWK': 0.54574332909784, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.3448168234985089, 'Micro_F1': 0.6136363636363636, 'Weighted_F1': 0.5827282700457503, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(125), 'FP_2': np.int64(0), 'FN_2': np.int64(7), 'TP_3': np.int64(25), 'TN_3': np.int64(76), 'FP_3': np.int64(17), 'FN_3': np.int64(14), 'TP_4': np.int64(49), 'TN_4': np.int64(40), 'FP_4': np.int64(29), 'FN_4': np.int64(14), 'TP_5': np.int64(7), 'TN_5': np.int64(105), 'FP_5': np.int64(5), 'FN_5': np.int64(15)}
-[2025-06-02 12:31:58,427][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-160
-[2025-06-02 12:31:58,428][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-160/config.json
-[2025-06-02 12:31:59,311][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-160/model.safetensors
-[2025-06-02 12:32:00,031][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-64] due to args.save_total_limit
-[2025-06-02 12:32:00,104][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-128] due to args.save_total_limit
-[2025-06-02 12:32:02,023][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:32:02,025][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:32:02,025][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:32:02,025][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:32:02,242][transformers][INFO] - {'accuracy': 0.5984848484848485, 'RMSE': 28.4977404739606, 'QWK': 0.45875152998776003, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2634544712127399, 'Micro_F1': 0.5984848484848485, 'Weighted_F1': 0.5182263632651547, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(125), 'FP_2': np.int64(0), 'FN_2': np.int64(7), 'TP_3': np.int64(24), 'TN_3': np.int64(77), 'FP_3': np.int64(16), 'FN_3': np.int64(15), 'TP_4': np.int64(55), 'TN_4': np.int64(32), 'FP_4': np.int64(37), 'FN_4': np.int64(8), 'TP_5': np.int64(0), 'TN_5': np.int64(110), 'FP_5': np.int64(0), 'FN_5': np.int64(22)}
-[2025-06-02 12:32:02,245][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-192
-[2025-06-02 12:32:02,246][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-192/config.json
-[2025-06-02 12:32:03,207][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-192/model.safetensors
-[2025-06-02 12:32:05,762][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:32:05,763][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:32:05,763][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:32:05,764][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:32:05,988][transformers][INFO] - {'accuracy': 0.5984848484848485, 'RMSE': 28.4977404739606, 'QWK': 0.46387002909796315, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.27667515923566877, 'Micro_F1': 0.5984848484848485, 'Weighted_F1': 0.5276970340346135, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(125), 'FP_2': np.int64(0), 'FN_2': np.int64(7), 'TP_3': np.int64(22), 'TN_3': np.int64(79), 'FP_3': np.int64(14), 'FN_3': np.int64(17), 'TP_4': np.int64(56), 'TN_4': np.int64(31), 'FP_4': np.int64(38), 'FN_4': np.int64(7), 'TP_5': np.int64(1), 'TN_5': np.int64(109), 'FP_5': np.int64(1), 'FN_5': np.int64(21)}
-[2025-06-02 12:32:05,991][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-224
-[2025-06-02 12:32:05,992][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-224/config.json
-[2025-06-02 12:32:06,916][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-224/model.safetensors
-[2025-06-02 12:32:07,611][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-192] due to args.save_total_limit
-[2025-06-02 12:32:09,521][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:32:09,523][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:32:09,523][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:32:09,523][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:32:09,739][transformers][INFO] - {'accuracy': 0.6666666666666666, 'RMSE': 25.34608929251695, 'QWK': 0.6442229454841335, 'HDIV': 0.0, 'Macro_F1': 0.43042272064701176, 'Micro_F1': 0.6666666666666666, 'Weighted_F1': 0.6472184106547204, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(1), 'TN_2': np.int64(124), 'FP_2': np.int64(1), 'FN_2': np.int64(6), 'TP_3': np.int64(27), 'TN_3': np.int64(78), 'FP_3': np.int64(15), 'FN_3': np.int64(12), 'TP_4': np.int64(51), 'TN_4': np.int64(44), 'FP_4': np.int64(25), 'FN_4': np.int64(12), 'TP_5': np.int64(9), 'TN_5': np.int64(107), 'FP_5': np.int64(3), 'FN_5': np.int64(13)}
-[2025-06-02 12:32:09,742][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-256
-[2025-06-02 12:32:09,744][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-256/config.json
-[2025-06-02 12:32:10,708][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-256/model.safetensors
-[2025-06-02 12:32:11,378][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-160] due to args.save_total_limit
-[2025-06-02 12:32:11,453][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-224] due to args.save_total_limit
-[2025-06-02 12:32:13,381][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:32:13,383][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:32:13,383][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:32:13,383][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:32:13,613][transformers][INFO] - {'accuracy': 0.6287878787878788, 'RMSE': 27.633971188310298, 'QWK': 0.5661519198664442, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.3633629589729778, 'Micro_F1': 0.6287878787878788, 'Weighted_F1': 0.6013413151172375, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(125), 'FP_2': np.int64(0), 'FN_2': np.int64(7), 'TP_3': np.int64(24), 'TN_3': np.int64(77), 'FP_3': np.int64(16), 'FN_3': np.int64(15), 'TP_4': np.int64(50), 'TN_4': np.int64(41), 'FP_4': np.int64(28), 'FN_4': np.int64(13), 'TP_5': np.int64(9), 'TN_5': np.int64(105), 'FP_5': np.int64(5), 'FN_5': np.int64(13)}
-[2025-06-02 12:32:13,616][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-288
-[2025-06-02 12:32:13,617][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-288/config.json
-[2025-06-02 12:32:14,431][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-288/model.safetensors
-[2025-06-02 12:32:17,073][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:32:17,075][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:32:17,075][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:32:17,075][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:32:17,293][transformers][INFO] - {'accuracy': 0.6287878787878788, 'RMSE': 27.633971188310298, 'QWK': 0.5508749189889824, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.3621000400160064, 'Micro_F1': 0.6287878787878788, 'Weighted_F1': 0.5978456837280367, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(125), 'FP_2': np.int64(0), 'FN_2': np.int64(7), 'TP_3': np.int64(21), 'TN_3': np.int64(78), 'FP_3': np.int64(15), 'FN_3': np.int64(18), 'TP_4': np.int64(53), 'TN_4': np.int64(38), 'FP_4': np.int64(31), 'FN_4': np.int64(10), 'TP_5': np.int64(9), 'TN_5': np.int64(107), 'FP_5': np.int64(3), 'FN_5': np.int64(13)}
-[2025-06-02 12:32:17,296][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-320
-[2025-06-02 12:32:17,297][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-320/config.json
-[2025-06-02 12:32:18,201][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-320/model.safetensors
-[2025-06-02 12:32:18,877][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-288] due to args.save_total_limit
-[2025-06-02 12:32:20,818][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:32:20,820][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:32:20,820][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:32:20,821][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:32:21,039][transformers][INFO] - {'accuracy': 0.5984848484848485, 'RMSE': 28.4977404739606, 'QWK': 0.4718107978977544, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2793621245966741, 'Micro_F1': 0.5984848484848485, 'Weighted_F1': 0.5303039704566138, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(125), 'FP_2': np.int64(0), 'FN_2': np.int64(7), 'TP_3': np.int64(24), 'TN_3': np.int64(77), 'FP_3': np.int64(16), 'FN_3': np.int64(15), 'TP_4': np.int64(54), 'TN_4': np.int64(33), 'FP_4': np.int64(36), 'FN_4': np.int64(9), 'TP_5': np.int64(1), 'TN_5': np.int64(109), 'FP_5': np.int64(1), 'FN_5': np.int64(21)}
-[2025-06-02 12:32:21,042][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-352
-[2025-06-02 12:32:21,043][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-352/config.json
-[2025-06-02 12:32:21,883][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-352/model.safetensors
-[2025-06-02 12:32:22,561][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-320] due to args.save_total_limit
-[2025-06-02 12:32:24,482][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:32:24,484][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:32:24,484][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:32:24,484][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:32:24,701][transformers][INFO] - {'accuracy': 0.5984848484848485, 'RMSE': 28.4977404739606, 'QWK': 0.4718107978977544, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2793621245966741, 'Micro_F1': 0.5984848484848485, 'Weighted_F1': 0.5303039704566138, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(125), 'FP_2': np.int64(0), 'FN_2': np.int64(7), 'TP_3': np.int64(24), 'TN_3': np.int64(77), 'FP_3': np.int64(16), 'FN_3': np.int64(15), 'TP_4': np.int64(54), 'TN_4': np.int64(33), 'FP_4': np.int64(36), 'FN_4': np.int64(9), 'TP_5': np.int64(1), 'TN_5': np.int64(109), 'FP_5': np.int64(1), 'FN_5': np.int64(21)}
-[2025-06-02 12:32:24,704][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-384
-[2025-06-02 12:32:24,705][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-384/config.json
-[2025-06-02 12:32:25,625][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-384/model.safetensors
-[2025-06-02 12:32:26,345][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-352] due to args.save_total_limit
-[2025-06-02 12:32:28,265][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:32:28,267][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:32:28,267][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:32:28,267][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:32:28,483][transformers][INFO] - {'accuracy': 0.5909090909090909, 'RMSE': 29.336088024923512, 'QWK': 0.5503742084052965, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.35156045108838185, 'Micro_F1': 0.5909090909090909, 'Weighted_F1': 0.5702560617981547, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(125), 'FP_2': np.int64(0), 'FN_2': np.int64(7), 'TP_3': np.int64(29), 'TN_3': np.int64(68), 'FP_3': np.int64(25), 'FN_3': np.int64(10), 'TP_4': np.int64(39), 'TN_4': np.int64(48), 'FP_4': np.int64(21), 'FN_4': np.int64(24), 'TP_5': np.int64(10), 'TN_5': np.int64(102), 'FP_5': np.int64(8), 'FN_5': np.int64(12)}
-[2025-06-02 12:32:28,486][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-416
-[2025-06-02 12:32:28,487][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-416/config.json
-[2025-06-02 12:32:29,421][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-416/model.safetensors
-[2025-06-02 12:32:30,135][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-384] due to args.save_total_limit
-[2025-06-02 12:32:30,209][transformers.trainer][INFO] - 
-
-Training completed. Do not forget to share your model on huggingface.co/models =)
-
-
-[2025-06-02 12:32:30,209][transformers.trainer][INFO] - Loading best model from /workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-256 (score: 0.6442229454841335).
-[2025-06-02 12:32:30,319][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-02/12-31-17/results/checkpoint-416] due to args.save_total_limit
-[2025-06-02 12:32:30,393][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:32:30,396][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:32:30,396][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-02 12:32:30,396][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:32:30,632][transformers][INFO] - {'accuracy': 0.6666666666666666, 'RMSE': 25.34608929251695, 'QWK': 0.6442229454841335, 'HDIV': 0.0, 'Macro_F1': 0.43042272064701176, 'Micro_F1': 0.6666666666666666, 'Weighted_F1': 0.6472184106547204, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(1), 'TN_2': np.int64(124), 'FP_2': np.int64(1), 'FN_2': np.int64(6), 'TP_3': np.int64(27), 'TN_3': np.int64(78), 'FP_3': np.int64(15), 'FN_3': np.int64(12), 'TP_4': np.int64(51), 'TN_4': np.int64(44), 'FP_4': np.int64(25), 'FN_4': np.int64(12), 'TP_5': np.int64(9), 'TN_5': np.int64(107), 'FP_5': np.int64(3), 'FN_5': np.int64(13)}
-[2025-06-02 12:32:30,635][__main__][INFO] - Training completed successfully.
-[2025-06-02 12:32:30,635][__main__][INFO] - Running on Test
-[2025-06-02 12:32:30,636][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text. If grades, id, essay_text, essay_year, reference, id_prompt, prompt, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-02 12:32:30,637][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-02 12:32:30,637][transformers.trainer][INFO] -   Num examples = 138
-[2025-06-02 12:32:30,637][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-02 12:32:30,862][transformers][INFO] - {'accuracy': 0.717391304347826, 'RMSE': 24.07717061715384, 'QWK': 0.6294307196562836, 'HDIV': 0.007246376811594235, 'Macro_F1': 0.39602986385595085, 'Micro_F1': 0.717391304347826, 'Weighted_F1': 0.685388223762515, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(138), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(4), 'TN_2': np.int64(124), 'FP_2': np.int64(4), 'FN_2': np.int64(6), 'TP_3': np.int64(52), 'TN_3': np.int64(58), 'FP_3': np.int64(14), 'FN_3': np.int64(14), 'TP_4': np.int64(43), 'TN_4': np.int64(66), 'FP_4': np.int64(21), 'FN_4': np.int64(8), 'TP_5': np.int64(0), 'TN_5': np.int64(128), 'FP_5': np.int64(0), 'FN_5': np.int64(10)}
-[2025-06-02 12:32:30,865][transformers.trainer][INFO] - Saving model checkpoint to ./results/best_model
-[2025-06-02 12:32:30,866][transformers.configuration_utils][INFO] - Configuration saved in ./results/best_model/config.json
-[2025-06-02 12:32:31,817][transformers.modeling_utils][INFO] - Model weights saved in ./results/best_model/model.safetensors
-[2025-06-02 12:32:31,818][transformers.tokenization_utils_base][INFO] - tokenizer config file saved in ./results/best_model/tokenizer_config.json
-[2025-06-02 12:32:31,818][transformers.tokenization_utils_base][INFO] - Special tokens file saved in ./results/best_model/special_tokens_map.json
-[2025-06-02 12:32:31,828][__main__][INFO] - Model and tokenizer saved to ./results/best_model
-[2025-06-02 12:32:31,830][__main__][INFO] - Fine Tuning Finished.
-[2025-06-02 12:32:32,339][__main__][INFO] - Total emissions: 0.0004 kg CO2eq
+version https://git-lfs.github.com/spec/v1
+oid sha256:6d8f2f32e63822236e7db4d0ae3f74fb36d7293319ab4d1570b505299ef2f77d
+size 44685

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C2/emissions.csv

@@ -1,2 +1,3 @@
-timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
-2025-06-03T00:53:21,jbcs2025,e839e4d0-70f8-4206-abef-ed15a38f26cd,bert-base-portuguese-cased-encoder_ordinal_coral-C2,46.12713149143383,0.00025497446575694407,5.527646257480694e-06,79.93125,215.63360864549884,70.0,0.0009496814137030796,0.00272311690071092,0.0008771484326183175,0.004549946747032317,France,FRA,île-de-france,,,Linux-5.15.0-136-generic-x86_64-with-glibc2.35,3.12.10,3.0.2,192,INTEL(R) XEON(R) PLATINUM 8568Y+,1,1 x NVIDIA H200,2.3494,48.8558,2015.3635139465332,machine,N,1.0
+version https://git-lfs.github.com/spec/v1
+oid sha256:52cafb9b520925fef393faddf911545fc4415837dc7ec6c537039f42800fd1cc
+size 851

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C2/evaluation_results.csv

@@ -1,4 +1,3 @@
-eval_loss,eval_model_preparation_time,eval_accuracy,eval_RMSE,eval_QWK,eval_HDIV,eval_Macro_F1,eval_Micro_F1,eval_Weighted_F1,eval_TP_0,eval_TN_0,eval_FP_0,eval_FN_0,eval_TP_1,eval_TN_1,eval_FP_1,eval_FN_1,eval_TP_2,eval_TN_2,eval_FP_2,eval_FN_2,eval_TP_3,eval_TN_3,eval_FP_3,eval_FN_3,eval_TP_4,eval_TN_4,eval_FP_4,eval_FN_4,eval_TP_5,eval_TN_5,eval_FP_5,eval_FN_5,eval_runtime,eval_samples_per_second,eval_steps_per_second,epoch,reference,timestamp,id
-25.99906349182129,0.0015,0.13636363636363635,70.83912632282966,-0.03175622097194419,0.12878787878787878,0.06502923976608187,0.13636363636363635,0.16116959064327485,0,131,0,1,2,77,30,23,0,71,61,0,16,48,23,45,0,102,0,30,0,117,0,15,0.6045,218.347,14.887,-1,validation_before_training,2025-06-03 00:52:41,bert-base-portuguese-cased-encoder_ordinal_coral-C2
-11.068385124206543,0.0015,0.45454545454545453,45.79268169663901,0.34769195612431436,0.007575757575757569,0.22453698933108812,0.45454545454545453,0.42546235949857597,0,131,0,1,3,104,3,22,0,118,14,0,45,26,45,16,11,93,9,19,1,116,1,14,0.2246,587.752,40.074,10.0,validation_after_training,2025-06-03 00:52:41,bert-base-portuguese-cased-encoder_ordinal_coral-C2
-14.555179595947266,0.0015,0.3115942028985507,57.38252018854179,0.1549805950840879,0.04347826086956519,0.17865937444138266,0.3115942028985507,0.24905337879030207,0,137,0,1,4,95,8,31,4,115,18,1,32,27,60,19,3,103,9,23,0,118,0,20,0.2237,616.972,40.237,10.0,test_results,2025-06-03 00:52:41,bert-base-portuguese-cased-encoder_ordinal_coral-C2
+version https://git-lfs.github.com/spec/v1
+oid sha256:3112b39dba03d0e6c7ed9484230a100a8129b1a4cd00c5301b7c040f8ebfe358
+size 1505

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C2/results/best_model/config.json

@@ -1,45 +1,3 @@
-{
-  "architectures": [
-    "BertForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cf1f6d6785c3b5bcfc91fad895c1ed8a279abdc99a665ea0767faf219a6e2d9
+size 1047

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C2/results/best_model/special_tokens_map.json

@@ -1,7 +1,3 @@
-{
-  "cls_token": "[CLS]",
-  "mask_token": "[MASK]",
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "unk_token": "[UNK]"
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6d346be366a7d1d48332dbc9fdf3bf8960b5d879522b7799ddba59e76237ee3
+size 125

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C2/results/best_model/tokenizer_config.json

@@ -1,58 +1,3 @@
-{
-  "added_tokens_decoder": {
-    "0": {
-      "content": "[PAD]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "100": {
-      "content": "[UNK]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "101": {
-      "content": "[CLS]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "102": {
-      "content": "[SEP]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "103": {
-      "content": "[MASK]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    }
-  },
-  "clean_up_tokenization_spaces": true,
-  "cls_token": "[CLS]",
-  "do_basic_tokenize": true,
-  "do_lower_case": false,
-  "extra_special_tokens": {},
-  "mask_token": "[MASK]",
-  "model_max_length": 1000000000000000019884624838656,
-  "never_split": null,
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "strip_accents": null,
-  "tokenize_chinese_chars": true,
-  "tokenizer_class": "BertTokenizer",
-  "unk_token": "[UNK]"
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ab044e4a71cdb2a5cff548e16d3bcd46a757848ef861743426c44a134b00da1
+size 1301

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C2/results/checkpoint-160/config.json

@@ -1,45 +1,3 @@
-{
-  "architectures": [
-    "BertForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cf1f6d6785c3b5bcfc91fad895c1ed8a279abdc99a665ea0767faf219a6e2d9
+size 1047

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C2/results/checkpoint-160/trainer_state.json

@@ -1,250 +1,3 @@
-{
-  "best_global_step": 160,
-  "best_metric": 0.34769195612431436,
-  "best_model_checkpoint": "/workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-160",
-  "epoch": 5.0,
-  "eval_steps": 500,
-  "global_step": 160,
-  "is_hyper_param_search": false,
-  "is_local_process_zero": true,
-  "is_world_process_zero": true,
-  "log_history": [
-    {
-      "epoch": 1.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 25,
-      "eval_FN_2": 0,
-      "eval_FN_3": 0,
-      "eval_FN_4": 30,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 71,
-      "eval_FP_4": 0,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.12642487046632125,
-      "eval_Micro_F1": 0.4621212121212121,
-      "eval_QWK": 0.0,
-      "eval_RMSE": 49.11335065052284,
-      "eval_TN_0": 131,
-      "eval_TN_1": 107,
-      "eval_TN_2": 132,
-      "eval_TN_3": 0,
-      "eval_TN_4": 102,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 61,
-      "eval_TP_4": 0,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.29211807191081807,
-      "eval_accuracy": 0.4621212121212121,
-      "eval_loss": 13.0120210647583,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2185,
-      "eval_samples_per_second": 604.034,
-      "eval_steps_per_second": 41.184,
-      "step": 32
-    },
-    {
-      "epoch": 2.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 25,
-      "eval_FN_2": 0,
-      "eval_FN_3": 0,
-      "eval_FN_4": 30,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 71,
-      "eval_FP_4": 0,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.12642487046632125,
-      "eval_Micro_F1": 0.4621212121212121,
-      "eval_QWK": 0.0,
-      "eval_RMSE": 49.11335065052284,
-      "eval_TN_0": 131,
-      "eval_TN_1": 107,
-      "eval_TN_2": 132,
-      "eval_TN_3": 0,
-      "eval_TN_4": 102,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 61,
-      "eval_TP_4": 0,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.29211807191081807,
-      "eval_accuracy": 0.4621212121212121,
-      "eval_loss": 10.990094184875488,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2217,
-      "eval_samples_per_second": 595.531,
-      "eval_steps_per_second": 40.604,
-      "step": 64
-    },
-    {
-      "epoch": 3.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 25,
-      "eval_FN_2": 0,
-      "eval_FN_3": 21,
-      "eval_FN_4": 6,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 26,
-      "eval_FP_4": 42,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.06060606060606055,
-      "eval_Macro_F1": 0.22598425196850394,
-      "eval_Micro_F1": 0.48484848484848486,
-      "eval_QWK": 0.2674418604651163,
-      "eval_RMSE": 47.86344211304794,
-      "eval_TN_0": 131,
-      "eval_TN_1": 107,
-      "eval_TN_2": 132,
-      "eval_TN_3": 45,
-      "eval_TN_4": 60,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 40,
-      "eval_TP_4": 24,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.4047363397757099,
-      "eval_accuracy": 0.48484848484848486,
-      "eval_loss": 12.508048057556152,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2186,
-      "eval_samples_per_second": 603.85,
-      "eval_steps_per_second": 41.172,
-      "step": 96
-    },
-    {
-      "epoch": 3.125,
-      "grad_norm": 139.40896606445312,
-      "learning_rate": 4.696180555555556e-05,
-      "loss": 13.8578,
-      "step": 100
-    },
-    {
-      "epoch": 4.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 25,
-      "eval_FN_2": 0,
-      "eval_FN_3": 0,
-      "eval_FN_4": 29,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 69,
-      "eval_FP_4": 1,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.14024869109947644,
-      "eval_Micro_F1": 0.4696969696969697,
-      "eval_QWK": 0.028825837609417593,
-      "eval_RMSE": 48.617243480439775,
-      "eval_TN_0": 131,
-      "eval_TN_1": 107,
-      "eval_TN_2": 132,
-      "eval_TN_3": 2,
-      "eval_TN_4": 101,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 61,
-      "eval_TP_4": 1,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.30938144534348727,
-      "eval_accuracy": 0.4696969696969697,
-      "eval_loss": 11.491454124450684,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2177,
-      "eval_samples_per_second": 606.302,
-      "eval_steps_per_second": 41.339,
-      "step": 128
-    },
-    {
-      "epoch": 5.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 22,
-      "eval_FN_2": 0,
-      "eval_FN_3": 16,
-      "eval_FN_4": 19,
-      "eval_FN_5": 14,
-      "eval_FP_0": 0,
-      "eval_FP_1": 3,
-      "eval_FP_2": 14,
-      "eval_FP_3": 45,
-      "eval_FP_4": 9,
-      "eval_FP_5": 1,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.22453698933108812,
-      "eval_Micro_F1": 0.45454545454545453,
-      "eval_QWK": 0.34769195612431436,
-      "eval_RMSE": 45.79268169663901,
-      "eval_TN_0": 131,
-      "eval_TN_1": 104,
-      "eval_TN_2": 118,
-      "eval_TN_3": 26,
-      "eval_TN_4": 93,
-      "eval_TN_5": 116,
-      "eval_TP_0": 0,
-      "eval_TP_1": 3,
-      "eval_TP_2": 0,
-      "eval_TP_3": 45,
-      "eval_TP_4": 11,
-      "eval_TP_5": 1,
-      "eval_Weighted_F1": 0.42546235949857597,
-      "eval_accuracy": 0.45454545454545453,
-      "eval_loss": 11.068385124206543,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2168,
-      "eval_samples_per_second": 608.806,
-      "eval_steps_per_second": 41.509,
-      "step": 160
-    }
-  ],
-  "logging_steps": 100,
-  "max_steps": 640,
-  "num_input_tokens_seen": 0,
-  "num_train_epochs": 20,
-  "save_steps": 500,
-  "stateful_callbacks": {
-    "EarlyStoppingCallback": {
-      "args": {
-        "early_stopping_patience": 5,
-        "early_stopping_threshold": 0.0
-      },
-      "attributes": {
-        "early_stopping_patience_counter": 0
-      }
-    },
-    "TrainerControl": {
-      "args": {
-        "should_epoch_stop": false,
-        "should_evaluate": false,
-        "should_log": false,
-        "should_save": true,
-        "should_training_stop": false
-      },
-      "attributes": {}
-    }
-  },
-  "total_flos": 657795356160000.0,
-  "train_batch_size": 16,
-  "trial_name": null,
-  "trial_params": null
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:b239ec390eb1f024944d95e12e671ea56c34297cd613b8aca700aa8f486e8ea7
+size 6621

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C2/run_experiment.log

@@ -1,340 +1,3 @@
-[2025-06-03 00:52:31,522][__main__][INFO] - cache_dir: /tmp/
-dataset:
-  name: kamel-usp/aes_enem_dataset
-  split: JBCS2025
-training_params:
-  seed: 42
-  num_train_epochs: 20
-  logging_steps: 100
-  metric_for_best_model: QWK
-  bf16: true
-post_training_results:
-  model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
-experiments:
-  model:
-    name: neuralmind/bert-base-portuguese-cased
-    type: encoder_ordinal_coral
-    num_labels: 6
-    output_dir: ./results/
-    logging_dir: ./logs/
-    best_model_dir: ./results/best_model
-  tokenizer:
-    name: neuralmind/bert-base-portuguese-cased
-  dataset:
-    grade_index: 1
-  training_params:
-    weight_decay: 0.01
-    warmup_ratio: 0.1
-    learning_rate: 5.0e-05
-    train_batch_size: 16
-    eval_batch_size: 16
-    gradient_accumulation_steps: 1
-    gradient_checkpointing: false
-
-[2025-06-03 00:52:35,426][__main__][INFO] - GPU 0: NVIDIA H200 | TDP ≈ 700 W
-[2025-06-03 00:52:35,426][__main__][INFO] - Starting the Fine Tuning training process.
-[2025-06-03 00:52:39,296][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 00:52:39,296][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 00:52:39,445][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
-[2025-06-03 00:52:39,446][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
-[2025-06-03 00:52:39,446][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
-[2025-06-03 00:52:39,446][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
-[2025-06-03 00:52:39,446][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
-[2025-06-03 00:52:39,446][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
-[2025-06-03 00:52:39,446][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 00:52:39,446][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 00:52:39,470][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 00:52:39,470][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 00:52:39,484][__main__][INFO] - Tokenizer function parameters- Padding:max_length; Truncation: True
-[2025-06-03 00:52:39,831][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 00:52:39,831][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 00:52:40,114][transformers.modeling_utils][INFO] - loading weights file pytorch_model.bin from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/pytorch_model.bin
-[2025-06-03 00:52:40,224][transformers.modeling_utils][INFO] - Since the `torch_dtype` attribute can't be found in model's config object, will use torch_dtype={torch_dtype} as derived from model's weights
-[2025-06-03 00:52:40,224][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
-[2025-06-03 00:52:40,484][transformers.safetensors_conversion][INFO] - Attempting to create safetensors variant
-[2025-06-03 00:52:41,026][transformers.modeling_utils][INFO] - Some weights of the model checkpoint at neuralmind/bert-base-portuguese-cased were not used when initializing BertForSequenceClassification: ['cls.predictions.bias', 'cls.predictions.decoder.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.dense.weight', 'cls.seq_relationship.bias', 'cls.seq_relationship.weight']
-- This IS expected if you are initializing BertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
-- This IS NOT expected if you are initializing BertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
-[2025-06-03 00:52:41,026][transformers.modeling_utils][WARNING] - Some weights of BertForSequenceClassification were not initialized from the model checkpoint at neuralmind/bert-base-portuguese-cased and are newly initialized: ['classifier.bias', 'classifier.weight']
-You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
-[2025-06-03 00:52:41,030][transformers.training_args][INFO] - PyTorch: setting up devices
-[2025-06-03 00:52:41,063][__main__][INFO] - Total steps: 620. Number of warmup steps: 62
-[2025-06-03 00:52:41,068][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
-[2025-06-03 00:52:41,084][transformers.trainer][INFO] - Using auto half precision backend
-[2025-06-03 00:52:41,086][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:52:41,089][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:52:41,089][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:52:41,089][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:52:41,172][transformers.safetensors_conversion][INFO] - Safetensors PR exists
-[2025-06-03 00:52:41,693][transformers][INFO] - {'accuracy': 0.13636363636363635, 'RMSE': 70.83912632282966, 'QWK': -0.03175622097194419, 'HDIV': 0.12878787878787878, 'Macro_F1': 0.06502923976608187, 'Micro_F1': 0.13636363636363635, 'Weighted_F1': 0.16116959064327485, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(2), 'TN_1': np.int64(77), 'FP_1': np.int64(30), 'FN_1': np.int64(23), 'TP_2': np.int64(0), 'TN_2': np.int64(71), 'FP_2': np.int64(61), 'FN_2': np.int64(0), 'TP_3': np.int64(16), 'TN_3': np.int64(48), 'FP_3': np.int64(23), 'FN_3': np.int64(45), 'TP_4': np.int64(0), 'TN_4': np.int64(102), 'FP_4': np.int64(0), 'FN_4': np.int64(30), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 00:52:41,864][transformers.trainer][INFO] - The following columns in the Training set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:52:41,870][transformers.trainer][INFO] - ***** Running training *****
-[2025-06-03 00:52:41,870][transformers.trainer][INFO] -   Num examples = 500
-[2025-06-03 00:52:41,870][transformers.trainer][INFO] -   Num Epochs = 20
-[2025-06-03 00:52:41,870][transformers.trainer][INFO] -   Instantaneous batch size per device = 16
-[2025-06-03 00:52:41,870][transformers.trainer][INFO] -   Total train batch size (w. parallel, distributed & accumulation) = 16
-[2025-06-03 00:52:41,870][transformers.trainer][INFO] -   Gradient Accumulation steps = 1
-[2025-06-03 00:52:41,870][transformers.trainer][INFO] -   Total optimization steps = 640
-[2025-06-03 00:52:41,870][transformers.trainer][INFO] -   Number of trainable parameters = 108,926,981
-[2025-06-03 00:52:43,948][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:52:43,950][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:52:43,950][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:52:43,950][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:52:44,169][transformers][INFO] - {'accuracy': 0.4621212121212121, 'RMSE': 49.11335065052284, 'QWK': 0.0, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.12642487046632125, 'Micro_F1': 0.4621212121212121, 'Weighted_F1': 0.29211807191081807, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(107), 'FP_1': np.int64(0), 'FN_1': np.int64(25), 'TP_2': np.int64(0), 'TN_2': np.int64(132), 'FP_2': np.int64(0), 'FN_2': np.int64(0), 'TP_3': np.int64(61), 'TN_3': np.int64(0), 'FP_3': np.int64(71), 'FN_3': np.int64(0), 'TP_4': np.int64(0), 'TN_4': np.int64(102), 'FP_4': np.int64(0), 'FN_4': np.int64(30), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 00:52:44,172][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-32
-[2025-06-03 00:52:44,173][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-32/config.json
-[2025-06-03 00:52:45,029][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-32/model.safetensors
-[2025-06-03 00:52:47,595][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:52:47,596][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:52:47,596][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:52:47,596][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:52:47,819][transformers][INFO] - {'accuracy': 0.4621212121212121, 'RMSE': 49.11335065052284, 'QWK': 0.0, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.12642487046632125, 'Micro_F1': 0.4621212121212121, 'Weighted_F1': 0.29211807191081807, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(107), 'FP_1': np.int64(0), 'FN_1': np.int64(25), 'TP_2': np.int64(0), 'TN_2': np.int64(132), 'FP_2': np.int64(0), 'FN_2': np.int64(0), 'TP_3': np.int64(61), 'TN_3': np.int64(0), 'FP_3': np.int64(71), 'FN_3': np.int64(0), 'TP_4': np.int64(0), 'TN_4': np.int64(102), 'FP_4': np.int64(0), 'FN_4': np.int64(30), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 00:52:47,821][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-64
-[2025-06-03 00:52:47,823][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-64/config.json
-[2025-06-03 00:52:48,612][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-64/model.safetensors
-[2025-06-03 00:52:51,122][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:52:51,124][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:52:51,124][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:52:51,124][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:52:51,343][transformers][INFO] - {'accuracy': 0.48484848484848486, 'RMSE': 47.86344211304794, 'QWK': 0.2674418604651163, 'HDIV': 0.06060606060606055, 'Macro_F1': 0.22598425196850394, 'Micro_F1': 0.48484848484848486, 'Weighted_F1': 0.4047363397757099, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(107), 'FP_1': np.int64(0), 'FN_1': np.int64(25), 'TP_2': np.int64(0), 'TN_2': np.int64(132), 'FP_2': np.int64(0), 'FN_2': np.int64(0), 'TP_3': np.int64(40), 'TN_3': np.int64(45), 'FP_3': np.int64(26), 'FN_3': np.int64(21), 'TP_4': np.int64(24), 'TN_4': np.int64(60), 'FP_4': np.int64(42), 'FN_4': np.int64(6), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 00:52:51,346][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-96
-[2025-06-03 00:52:51,347][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-96/config.json
-[2025-06-03 00:52:52,182][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-96/model.safetensors
-[2025-06-03 00:52:52,859][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-32] due to args.save_total_limit
-[2025-06-03 00:52:52,945][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-64] due to args.save_total_limit
-[2025-06-03 00:52:54,878][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:52:54,880][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:52:54,880][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:52:54,880][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:52:55,099][transformers][INFO] - {'accuracy': 0.4696969696969697, 'RMSE': 48.617243480439775, 'QWK': 0.028825837609417593, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.14024869109947644, 'Micro_F1': 0.4696969696969697, 'Weighted_F1': 0.30938144534348727, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(107), 'FP_1': np.int64(0), 'FN_1': np.int64(25), 'TP_2': np.int64(0), 'TN_2': np.int64(132), 'FP_2': np.int64(0), 'FN_2': np.int64(0), 'TP_3': np.int64(61), 'TN_3': np.int64(2), 'FP_3': np.int64(69), 'FN_3': np.int64(0), 'TP_4': np.int64(1), 'TN_4': np.int64(101), 'FP_4': np.int64(1), 'FN_4': np.int64(29), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 00:52:55,102][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-128
-[2025-06-03 00:52:55,103][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-128/config.json
-[2025-06-03 00:52:56,003][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-128/model.safetensors
-[2025-06-03 00:52:58,531][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:52:58,532][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:52:58,532][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:52:58,532][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:52:58,750][transformers][INFO] - {'accuracy': 0.45454545454545453, 'RMSE': 45.79268169663901, 'QWK': 0.34769195612431436, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.22453698933108812, 'Micro_F1': 0.45454545454545453, 'Weighted_F1': 0.42546235949857597, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(3), 'TN_1': np.int64(104), 'FP_1': np.int64(3), 'FN_1': np.int64(22), 'TP_2': np.int64(0), 'TN_2': np.int64(118), 'FP_2': np.int64(14), 'FN_2': np.int64(0), 'TP_3': np.int64(45), 'TN_3': np.int64(26), 'FP_3': np.int64(45), 'FN_3': np.int64(16), 'TP_4': np.int64(11), 'TN_4': np.int64(93), 'FP_4': np.int64(9), 'FN_4': np.int64(19), 'TP_5': np.int64(1), 'TN_5': np.int64(116), 'FP_5': np.int64(1), 'FN_5': np.int64(14)}
-[2025-06-03 00:52:58,753][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-160
-[2025-06-03 00:52:58,754][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-160/config.json
-[2025-06-03 00:52:59,675][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-160/model.safetensors
-[2025-06-03 00:53:00,338][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-96] due to args.save_total_limit
-[2025-06-03 00:53:00,401][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-128] due to args.save_total_limit
-[2025-06-03 00:53:02,332][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:53:02,334][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:53:02,334][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:53:02,334][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:53:02,553][transformers][INFO] - {'accuracy': 0.5075757575757576, 'RMSE': 45.26019054848144, 'QWK': 0.2602467170712296, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.1999011027718319, 'Micro_F1': 0.5075757575757576, 'Weighted_F1': 0.41391404767593565, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(107), 'FP_1': np.int64(0), 'FN_1': np.int64(25), 'TP_2': np.int64(0), 'TN_2': np.int64(130), 'FP_2': np.int64(2), 'FN_2': np.int64(0), 'TP_3': np.int64(55), 'TN_3': np.int64(20), 'FP_3': np.int64(51), 'FN_3': np.int64(6), 'TP_4': np.int64(11), 'TN_4': np.int64(91), 'FP_4': np.int64(11), 'FN_4': np.int64(19), 'TP_5': np.int64(1), 'TN_5': np.int64(116), 'FP_5': np.int64(1), 'FN_5': np.int64(14)}
-[2025-06-03 00:53:02,556][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-192
-[2025-06-03 00:53:02,557][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-192/config.json
-[2025-06-03 00:53:03,334][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-192/model.safetensors
-[2025-06-03 00:53:05,892][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:53:05,894][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:53:05,894][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:53:05,894][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:53:06,122][transformers][INFO] - {'accuracy': 0.5378787878787878, 'RMSE': 46.056618647183825, 'QWK': 0.25589485890993435, 'HDIV': 0.022727272727272707, 'Macro_F1': 0.26260427482009235, 'Micro_F1': 0.5378787878787878, 'Weighted_F1': 0.444564690259438, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(107), 'FP_1': np.int64(0), 'FN_1': np.int64(25), 'TP_2': np.int64(0), 'TN_2': np.int64(132), 'FP_2': np.int64(0), 'FN_2': np.int64(0), 'TP_3': np.int64(54), 'TN_3': np.int64(27), 'FP_3': np.int64(44), 'FN_3': np.int64(7), 'TP_4': np.int64(16), 'TN_4': np.int64(86), 'FP_4': np.int64(16), 'FN_4': np.int64(14), 'TP_5': np.int64(1), 'TN_5': np.int64(116), 'FP_5': np.int64(1), 'FN_5': np.int64(14)}
-[2025-06-03 00:53:06,125][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-224
-[2025-06-03 00:53:06,126][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-224/config.json
-[2025-06-03 00:53:06,907][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-224/model.safetensors
-[2025-06-03 00:53:07,628][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-192] due to args.save_total_limit
-[2025-06-03 00:53:09,559][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:53:09,561][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:53:09,561][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:53:09,561][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:53:09,783][transformers][INFO] - {'accuracy': 0.5, 'RMSE': 46.83950676447601, 'QWK': 0.2820913461538461, 'HDIV': 0.037878787878787845, 'Macro_F1': 0.22012173290368778, 'Micro_F1': 0.5, 'Weighted_F1': 0.4296129935227679, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(107), 'FP_1': np.int64(0), 'FN_1': np.int64(25), 'TP_2': np.int64(0), 'TN_2': np.int64(130), 'FP_2': np.int64(2), 'FN_2': np.int64(0), 'TP_3': np.int64(48), 'TN_3': np.int64(33), 'FP_3': np.int64(38), 'FN_3': np.int64(13), 'TP_4': np.int64(16), 'TN_4': np.int64(78), 'FP_4': np.int64(24), 'FN_4': np.int64(14), 'TP_5': np.int64(2), 'TN_5': np.int64(115), 'FP_5': np.int64(2), 'FN_5': np.int64(13)}
-[2025-06-03 00:53:09,786][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-256
-[2025-06-03 00:53:09,787][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-256/config.json
-[2025-06-03 00:53:10,710][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-256/model.safetensors
-[2025-06-03 00:53:11,379][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-224] due to args.save_total_limit
-[2025-06-03 00:53:13,306][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:53:13,308][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:53:13,308][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:53:13,308][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:53:13,527][transformers][INFO] - {'accuracy': 0.5303030303030303, 'RMSE': 44.44949466256704, 'QWK': 0.30160997143599055, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2576909024479357, 'Micro_F1': 0.5303030303030303, 'Weighted_F1': 0.43699970106619723, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(107), 'FP_1': np.int64(0), 'FN_1': np.int64(25), 'TP_2': np.int64(0), 'TN_2': np.int64(132), 'FP_2': np.int64(0), 'FN_2': np.int64(0), 'TP_3': np.int64(54), 'TN_3': np.int64(25), 'FP_3': np.int64(46), 'FN_3': np.int64(7), 'TP_4': np.int64(15), 'TN_4': np.int64(87), 'FP_4': np.int64(15), 'FN_4': np.int64(15), 'TP_5': np.int64(1), 'TN_5': np.int64(116), 'FP_5': np.int64(1), 'FN_5': np.int64(14)}
-[2025-06-03 00:53:13,530][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-288
-[2025-06-03 00:53:13,531][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-288/config.json
-[2025-06-03 00:53:14,411][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-288/model.safetensors
-[2025-06-03 00:53:15,111][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-256] due to args.save_total_limit
-[2025-06-03 00:53:17,027][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:53:17,029][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:53:17,029][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:53:17,029][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:53:17,249][transformers][INFO] - {'accuracy': 0.5075757575757576, 'RMSE': 46.31905164675272, 'QWK': 0.2917424518006547, 'HDIV': 0.037878787878787845, 'Macro_F1': 0.2124982860276978, 'Micro_F1': 0.5075757575757576, 'Weighted_F1': 0.4307773331837503, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(107), 'FP_1': np.int64(0), 'FN_1': np.int64(25), 'TP_2': np.int64(0), 'TN_2': np.int64(130), 'FP_2': np.int64(2), 'FN_2': np.int64(0), 'TP_3': np.int64(47), 'TN_3': np.int64(36), 'FP_3': np.int64(35), 'FN_3': np.int64(14), 'TP_4': np.int64(19), 'TN_4': np.int64(75), 'FP_4': np.int64(27), 'FN_4': np.int64(11), 'TP_5': np.int64(1), 'TN_5': np.int64(116), 'FP_5': np.int64(1), 'FN_5': np.int64(14)}
-[2025-06-03 00:53:17,252][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-320
-[2025-06-03 00:53:17,253][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-320/config.json
-[2025-06-03 00:53:18,195][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-320/model.safetensors
-[2025-06-03 00:53:18,916][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-288] due to args.save_total_limit
-[2025-06-03 00:53:18,995][transformers.trainer][INFO] - 
-
-Training completed. Do not forget to share your model on huggingface.co/models =)
-
-
-[2025-06-03 00:53:18,995][transformers.trainer][INFO] - Loading best model from /workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-160 (score: 0.34769195612431436).
-[2025-06-03 00:53:19,130][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/00-52-31/results/checkpoint-320] due to args.save_total_limit
-[2025-06-03 00:53:19,213][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:53:19,215][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:53:19,215][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 00:53:19,215][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:53:19,440][transformers][INFO] - {'accuracy': 0.45454545454545453, 'RMSE': 45.79268169663901, 'QWK': 0.34769195612431436, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.22453698933108812, 'Micro_F1': 0.45454545454545453, 'Weighted_F1': 0.42546235949857597, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(3), 'TN_1': np.int64(104), 'FP_1': np.int64(3), 'FN_1': np.int64(22), 'TP_2': np.int64(0), 'TN_2': np.int64(118), 'FP_2': np.int64(14), 'FN_2': np.int64(0), 'TP_3': np.int64(45), 'TN_3': np.int64(26), 'FP_3': np.int64(45), 'FN_3': np.int64(16), 'TP_4': np.int64(11), 'TN_4': np.int64(93), 'FP_4': np.int64(9), 'FN_4': np.int64(19), 'TP_5': np.int64(1), 'TN_5': np.int64(116), 'FP_5': np.int64(1), 'FN_5': np.int64(14)}
-[2025-06-03 00:53:19,445][__main__][INFO] - Training completed successfully.
-[2025-06-03 00:53:19,445][__main__][INFO] - Running on Test
-[2025-06-03 00:53:19,445][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference. If essay_text, prompt, supporting_text, grades, id, id_prompt, essay_year, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 00:53:19,447][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 00:53:19,447][transformers.trainer][INFO] -   Num examples = 138
-[2025-06-03 00:53:19,447][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 00:53:19,671][transformers][INFO] - {'accuracy': 0.3115942028985507, 'RMSE': 57.38252018854179, 'QWK': 0.1549805950840879, 'HDIV': 0.04347826086956519, 'Macro_F1': 0.17865937444138266, 'Micro_F1': 0.3115942028985507, 'Weighted_F1': 0.24905337879030207, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(4), 'TN_1': np.int64(95), 'FP_1': np.int64(8), 'FN_1': np.int64(31), 'TP_2': np.int64(4), 'TN_2': np.int64(115), 'FP_2': np.int64(18), 'FN_2': np.int64(1), 'TP_3': np.int64(32), 'TN_3': np.int64(27), 'FP_3': np.int64(60), 'FN_3': np.int64(19), 'TP_4': np.int64(3), 'TN_4': np.int64(103), 'FP_4': np.int64(9), 'FN_4': np.int64(23), 'TP_5': np.int64(0), 'TN_5': np.int64(118), 'FP_5': np.int64(0), 'FN_5': np.int64(20)}
-[2025-06-03 00:53:19,673][transformers.trainer][INFO] - Saving model checkpoint to ./results/best_model
-[2025-06-03 00:53:19,675][transformers.configuration_utils][INFO] - Configuration saved in ./results/best_model/config.json
-[2025-06-03 00:53:20,528][transformers.modeling_utils][INFO] - Model weights saved in ./results/best_model/model.safetensors
-[2025-06-03 00:53:20,529][transformers.tokenization_utils_base][INFO] - tokenizer config file saved in ./results/best_model/tokenizer_config.json
-[2025-06-03 00:53:20,529][transformers.tokenization_utils_base][INFO] - Special tokens file saved in ./results/best_model/special_tokens_map.json
-[2025-06-03 00:53:20,539][__main__][INFO] - Model and tokenizer saved to ./results/best_model
-[2025-06-03 00:53:20,542][__main__][INFO] - Fine Tuning Finished.
-[2025-06-03 00:53:21,051][__main__][INFO] - Total emissions: 0.0003 kg CO2eq
+version https://git-lfs.github.com/spec/v1
+oid sha256:4aab615063e5c6cc16907eda02c99c8a9acf1ef71a332ef4591e05e952a68eb0
+size 38211

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C3/emissions.csv

@@ -1,2 +1,3 @@
-timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
-2025-06-03T01:13:33,jbcs2025,8412240e-49bf-4209-b9ff-4318a0974ed9,bert-base-portuguese-cased-encoder_ordinal_coral-C3,46.182801492046565,0.00025397754784985864,5.499396737410955e-06,76.34375,214.91076191889516,70.0,0.0009294414904217736,0.0027251596801534106,0.0008775558602401158,0.0045321570308153,France,FRA,île-de-france,,,Linux-5.15.0-136-generic-x86_64-with-glibc2.35,3.12.10,3.0.2,192,INTEL(R) XEON(R) PLATINUM 8568Y+,1,1 x NVIDIA H200,2.3494,48.8558,2015.3635139465332,machine,N,1.0
+version https://git-lfs.github.com/spec/v1
+oid sha256:36c6aac82843384914013c32f4b4aecf83d80d8c7aece2c2b4887bc610f13644
+size 852

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C3/evaluation_results.csv

@@ -1,4 +1,3 @@
-eval_loss,eval_model_preparation_time,eval_accuracy,eval_RMSE,eval_QWK,eval_HDIV,eval_Macro_F1,eval_Micro_F1,eval_Weighted_F1,eval_TP_0,eval_TN_0,eval_FP_0,eval_FN_0,eval_TP_1,eval_TN_1,eval_FP_1,eval_FN_1,eval_TP_2,eval_TN_2,eval_FP_2,eval_FN_2,eval_TP_3,eval_TN_3,eval_FP_3,eval_FN_3,eval_TP_4,eval_TN_4,eval_FP_4,eval_FN_4,eval_TP_5,eval_TN_5,eval_FP_5,eval_FN_5,eval_runtime,eval_samples_per_second,eval_steps_per_second,epoch,reference,timestamp,id
-25.971601486206055,0.0015,0.16666666666666666,70.15135152805055,-0.0969828468497973,0.15909090909090906,0.08977627390995334,0.16666666666666666,0.15807186540476612,0,131,0,1,2,78,30,22,4,69,57,2,16,56,23,37,0,92,0,40,0,124,0,8,0.5595,235.93,16.086,-1,validation_before_training,2025-06-03 01:12:53,bert-base-portuguese-cased-encoder_ordinal_coral-C3
-10.606083869934082,0.0015,0.36363636363636365,44.17595671307132,0.4778891509433961,0.007575757575757569,0.20135414869760224,0.36363636363636365,0.3738767701162043,0,131,0,1,7,95,13,17,0,102,24,6,28,41,38,25,13,83,9,27,0,124,0,8,0.2384,553.633,37.748,10.0,validation_after_training,2025-06-03 01:12:53,bert-base-portuguese-cased-encoder_ordinal_coral-C3
-12.71513557434082,0.0015,0.2608695652173913,52.1980620440972,0.33263365847635495,0.036231884057971064,0.16607083828156566,0.2608695652173913,0.25270416127040973,0,137,0,1,8,85,24,21,4,90,30,14,18,53,40,27,6,92,8,32,0,131,0,7,0.2285,603.839,39.381,10.0,test_results,2025-06-03 01:12:53,bert-base-portuguese-cased-encoder_ordinal_coral-C3
+version https://git-lfs.github.com/spec/v1
+oid sha256:54add906ef4b25dc9cb20272820a6254c93c3bbb66a2b5d3b38fb59b2ba719f5
+size 1498

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C3/results/best_model/config.json

@@ -1,45 +1,3 @@
-{
-  "architectures": [
-    "BertForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cf1f6d6785c3b5bcfc91fad895c1ed8a279abdc99a665ea0767faf219a6e2d9
+size 1047

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C3/results/best_model/special_tokens_map.json

@@ -1,7 +1,3 @@
-{
-  "cls_token": "[CLS]",
-  "mask_token": "[MASK]",
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "unk_token": "[UNK]"
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6d346be366a7d1d48332dbc9fdf3bf8960b5d879522b7799ddba59e76237ee3
+size 125

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C3/results/best_model/tokenizer_config.json

@@ -1,58 +1,3 @@
-{
-  "added_tokens_decoder": {
-    "0": {
-      "content": "[PAD]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "100": {
-      "content": "[UNK]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "101": {
-      "content": "[CLS]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "102": {
-      "content": "[SEP]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "103": {
-      "content": "[MASK]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    }
-  },
-  "clean_up_tokenization_spaces": true,
-  "cls_token": "[CLS]",
-  "do_basic_tokenize": true,
-  "do_lower_case": false,
-  "extra_special_tokens": {},
-  "mask_token": "[MASK]",
-  "model_max_length": 1000000000000000019884624838656,
-  "never_split": null,
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "strip_accents": null,
-  "tokenize_chinese_chars": true,
-  "tokenizer_class": "BertTokenizer",
-  "unk_token": "[UNK]"
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ab044e4a71cdb2a5cff548e16d3bcd46a757848ef861743426c44a134b00da1
+size 1301

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C3/results/checkpoint-160/config.json

@@ -1,45 +1,3 @@
-{
-  "architectures": [
-    "BertForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cf1f6d6785c3b5bcfc91fad895c1ed8a279abdc99a665ea0767faf219a6e2d9
+size 1047

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C3/results/checkpoint-160/trainer_state.json

@@ -1,250 +1,3 @@
-{
-  "best_global_step": 160,
-  "best_metric": 0.4778891509433961,
-  "best_model_checkpoint": "/workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-160",
-  "epoch": 5.0,
-  "eval_steps": 500,
-  "global_step": 160,
-  "is_hyper_param_search": false,
-  "is_local_process_zero": true,
-  "is_world_process_zero": true,
-  "log_history": [
-    {
-      "epoch": 1.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 24,
-      "eval_FN_2": 6,
-      "eval_FN_3": 0,
-      "eval_FN_4": 40,
-      "eval_FN_5": 8,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 79,
-      "eval_FP_4": 0,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.0954954954954955,
-      "eval_Micro_F1": 0.4015151515151515,
-      "eval_QWK": 0.0,
-      "eval_RMSE": 47.09757762541316,
-      "eval_TN_0": 131,
-      "eval_TN_1": 108,
-      "eval_TN_2": 126,
-      "eval_TN_3": 0,
-      "eval_TN_4": 92,
-      "eval_TN_5": 124,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 53,
-      "eval_TP_4": 0,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.23005733005733006,
-      "eval_accuracy": 0.4015151515151515,
-      "eval_loss": 12.790568351745605,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2251,
-      "eval_samples_per_second": 586.461,
-      "eval_steps_per_second": 39.986,
-      "step": 32
-    },
-    {
-      "epoch": 2.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 24,
-      "eval_FN_2": 1,
-      "eval_FN_3": 30,
-      "eval_FN_4": 40,
-      "eval_FN_5": 8,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 55,
-      "eval_FP_3": 49,
-      "eval_FP_4": 0,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.0,
-      "eval_Macro_F1": 0.08658585858585859,
-      "eval_Micro_F1": 0.21212121212121213,
-      "eval_QWK": 0.28539241457003384,
-      "eval_RMSE": 45.79268169663901,
-      "eval_TN_0": 131,
-      "eval_TN_1": 108,
-      "eval_TN_2": 71,
-      "eval_TN_3": 30,
-      "eval_TN_4": 92,
-      "eval_TN_5": 124,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 5,
-      "eval_TP_3": 23,
-      "eval_TP_4": 0,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.15464462809917356,
-      "eval_accuracy": 0.21212121212121213,
-      "eval_loss": 11.326273918151855,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2149,
-      "eval_samples_per_second": 614.14,
-      "eval_steps_per_second": 41.873,
-      "step": 64
-    },
-    {
-      "epoch": 3.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 24,
-      "eval_FN_2": 2,
-      "eval_FN_3": 27,
-      "eval_FN_4": 8,
-      "eval_FN_5": 8,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 16,
-      "eval_FP_3": 18,
-      "eval_FP_4": 36,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.06060606060606055,
-      "eval_Macro_F1": 0.23939456241861742,
-      "eval_Micro_F1": 0.4696969696969697,
-      "eval_QWK": 0.37069253931080626,
-      "eval_RMSE": 45.52721463835969,
-      "eval_TN_0": 131,
-      "eval_TN_1": 108,
-      "eval_TN_2": 110,
-      "eval_TN_3": 61,
-      "eval_TN_4": 56,
-      "eval_TN_5": 124,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 4,
-      "eval_TP_3": 26,
-      "eval_TP_4": 32,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.4088047627566528,
-      "eval_accuracy": 0.4696969696969697,
-      "eval_loss": 10.207509994506836,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.214,
-      "eval_samples_per_second": 616.8,
-      "eval_steps_per_second": 42.055,
-      "step": 96
-    },
-    {
-      "epoch": 3.125,
-      "grad_norm": 47.49462127685547,
-      "learning_rate": 4.696180555555556e-05,
-      "loss": 13.5857,
-      "step": 100
-    },
-    {
-      "epoch": 4.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 24,
-      "eval_FN_2": 2,
-      "eval_FN_3": 15,
-      "eval_FN_4": 20,
-      "eval_FN_5": 8,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 16,
-      "eval_FP_3": 36,
-      "eval_FP_4": 18,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.022727272727272707,
-      "eval_Macro_F1": 0.23648966956053571,
-      "eval_Micro_F1": 0.4696969696969697,
-      "eval_QWK": 0.39902034664657116,
-      "eval_RMSE": 41.92345116490003,
-      "eval_TN_0": 131,
-      "eval_TN_1": 108,
-      "eval_TN_2": 110,
-      "eval_TN_3": 43,
-      "eval_TN_4": 74,
-      "eval_TN_5": 124,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 4,
-      "eval_TP_3": 38,
-      "eval_TP_4": 20,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.4096629529700396,
-      "eval_accuracy": 0.4696969696969697,
-      "eval_loss": 9.977594375610352,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2172,
-      "eval_samples_per_second": 607.805,
-      "eval_steps_per_second": 41.441,
-      "step": 128
-    },
-    {
-      "epoch": 5.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 17,
-      "eval_FN_2": 6,
-      "eval_FN_3": 25,
-      "eval_FN_4": 27,
-      "eval_FN_5": 8,
-      "eval_FP_0": 0,
-      "eval_FP_1": 13,
-      "eval_FP_2": 24,
-      "eval_FP_3": 38,
-      "eval_FP_4": 9,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.20135414869760224,
-      "eval_Micro_F1": 0.36363636363636365,
-      "eval_QWK": 0.4778891509433961,
-      "eval_RMSE": 44.17595671307132,
-      "eval_TN_0": 131,
-      "eval_TN_1": 95,
-      "eval_TN_2": 102,
-      "eval_TN_3": 41,
-      "eval_TN_4": 83,
-      "eval_TN_5": 124,
-      "eval_TP_0": 0,
-      "eval_TP_1": 7,
-      "eval_TP_2": 0,
-      "eval_TP_3": 28,
-      "eval_TP_4": 13,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.3738767701162043,
-      "eval_accuracy": 0.36363636363636365,
-      "eval_loss": 10.606083869934082,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2173,
-      "eval_samples_per_second": 607.49,
-      "eval_steps_per_second": 41.42,
-      "step": 160
-    }
-  ],
-  "logging_steps": 100,
-  "max_steps": 640,
-  "num_input_tokens_seen": 0,
-  "num_train_epochs": 20,
-  "save_steps": 500,
-  "stateful_callbacks": {
-    "EarlyStoppingCallback": {
-      "args": {
-        "early_stopping_patience": 5,
-        "early_stopping_threshold": 0.0
-      },
-      "attributes": {
-        "early_stopping_patience_counter": 0
-      }
-    },
-    "TrainerControl": {
-      "args": {
-        "should_epoch_stop": false,
-        "should_evaluate": false,
-        "should_log": false,
-        "should_save": true,
-        "should_training_stop": false
-      },
-      "attributes": {}
-    }
-  },
-  "total_flos": 657795356160000.0,
-  "train_batch_size": 16,
-  "trial_name": null,
-  "trial_params": null
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:d27ab556327517d3be59bce4a958f11dc26a600685893e409820271548f5883a
+size 6609

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C3/run_experiment.log

@@ -1,340 +1,3 @@
-[2025-06-03 01:12:43,892][__main__][INFO] - cache_dir: /tmp/
-dataset:
-  name: kamel-usp/aes_enem_dataset
-  split: JBCS2025
-training_params:
-  seed: 42
-  num_train_epochs: 20
-  logging_steps: 100
-  metric_for_best_model: QWK
-  bf16: true
-post_training_results:
-  model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
-experiments:
-  model:
-    name: neuralmind/bert-base-portuguese-cased
-    type: encoder_ordinal_coral
-    num_labels: 6
-    output_dir: ./results/
-    logging_dir: ./logs/
-    best_model_dir: ./results/best_model
-  tokenizer:
-    name: neuralmind/bert-base-portuguese-cased
-  dataset:
-    grade_index: 2
-  training_params:
-    weight_decay: 0.01
-    warmup_ratio: 0.1
-    learning_rate: 5.0e-05
-    train_batch_size: 16
-    eval_batch_size: 16
-    gradient_accumulation_steps: 1
-    gradient_checkpointing: false
-
-[2025-06-03 01:12:47,758][__main__][INFO] - GPU 0: NVIDIA H200 | TDP ≈ 700 W
-[2025-06-03 01:12:47,759][__main__][INFO] - Starting the Fine Tuning training process.
-[2025-06-03 01:12:51,222][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 01:12:51,223][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 01:12:51,362][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
-[2025-06-03 01:12:51,363][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
-[2025-06-03 01:12:51,363][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
-[2025-06-03 01:12:51,363][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
-[2025-06-03 01:12:51,363][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
-[2025-06-03 01:12:51,363][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
-[2025-06-03 01:12:51,363][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 01:12:51,363][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 01:12:51,386][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 01:12:51,387][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 01:12:51,401][__main__][INFO] - Tokenizer function parameters- Padding:max_length; Truncation: True
-[2025-06-03 01:12:51,727][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 01:12:51,728][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 01:12:52,137][transformers.modeling_utils][INFO] - loading weights file pytorch_model.bin from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/pytorch_model.bin
-[2025-06-03 01:12:52,240][transformers.modeling_utils][INFO] - Since the `torch_dtype` attribute can't be found in model's config object, will use torch_dtype={torch_dtype} as derived from model's weights
-[2025-06-03 01:12:52,240][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
-[2025-06-03 01:12:52,340][transformers.safetensors_conversion][INFO] - Attempting to create safetensors variant
-[2025-06-03 01:12:52,856][transformers.safetensors_conversion][INFO] - Safetensors PR exists
-[2025-06-03 01:12:52,969][transformers.modeling_utils][INFO] - Some weights of the model checkpoint at neuralmind/bert-base-portuguese-cased were not used when initializing BertForSequenceClassification: ['cls.predictions.bias', 'cls.predictions.decoder.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.dense.weight', 'cls.seq_relationship.bias', 'cls.seq_relationship.weight']
-- This IS expected if you are initializing BertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
-- This IS NOT expected if you are initializing BertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
-[2025-06-03 01:12:52,969][transformers.modeling_utils][WARNING] - Some weights of BertForSequenceClassification were not initialized from the model checkpoint at neuralmind/bert-base-portuguese-cased and are newly initialized: ['classifier.bias', 'classifier.weight']
-You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
-[2025-06-03 01:12:52,973][transformers.training_args][INFO] - PyTorch: setting up devices
-[2025-06-03 01:12:53,008][__main__][INFO] - Total steps: 620. Number of warmup steps: 62
-[2025-06-03 01:12:53,013][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
-[2025-06-03 01:12:53,029][transformers.trainer][INFO] - Using auto half precision backend
-[2025-06-03 01:12:53,031][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:12:53,035][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:12:53,035][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:12:53,035][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:12:53,594][transformers][INFO] - {'accuracy': 0.16666666666666666, 'RMSE': 70.15135152805055, 'QWK': -0.0969828468497973, 'HDIV': 0.15909090909090906, 'Macro_F1': 0.08977627390995334, 'Micro_F1': 0.16666666666666666, 'Weighted_F1': 0.15807186540476612, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(2), 'TN_1': np.int64(78), 'FP_1': np.int64(30), 'FN_1': np.int64(22), 'TP_2': np.int64(4), 'TN_2': np.int64(69), 'FP_2': np.int64(57), 'FN_2': np.int64(2), 'TP_3': np.int64(16), 'TN_3': np.int64(56), 'FP_3': np.int64(23), 'FN_3': np.int64(37), 'TP_4': np.int64(0), 'TN_4': np.int64(92), 'FP_4': np.int64(0), 'FN_4': np.int64(40), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:12:53,750][transformers.trainer][INFO] - The following columns in the Training set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:12:53,756][transformers.trainer][INFO] - ***** Running training *****
-[2025-06-03 01:12:53,756][transformers.trainer][INFO] -   Num examples = 500
-[2025-06-03 01:12:53,756][transformers.trainer][INFO] -   Num Epochs = 20
-[2025-06-03 01:12:53,756][transformers.trainer][INFO] -   Instantaneous batch size per device = 16
-[2025-06-03 01:12:53,756][transformers.trainer][INFO] -   Total train batch size (w. parallel, distributed & accumulation) = 16
-[2025-06-03 01:12:53,756][transformers.trainer][INFO] -   Gradient Accumulation steps = 1
-[2025-06-03 01:12:53,756][transformers.trainer][INFO] -   Total optimization steps = 640
-[2025-06-03 01:12:53,756][transformers.trainer][INFO] -   Number of trainable parameters = 108,926,981
-[2025-06-03 01:12:55,785][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:12:55,787][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:12:55,787][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:12:55,787][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:12:56,013][transformers][INFO] - {'accuracy': 0.4015151515151515, 'RMSE': 47.09757762541316, 'QWK': 0.0, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.0954954954954955, 'Micro_F1': 0.4015151515151515, 'Weighted_F1': 0.23005733005733006, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(108), 'FP_1': np.int64(0), 'FN_1': np.int64(24), 'TP_2': np.int64(0), 'TN_2': np.int64(126), 'FP_2': np.int64(0), 'FN_2': np.int64(6), 'TP_3': np.int64(53), 'TN_3': np.int64(0), 'FP_3': np.int64(79), 'FN_3': np.int64(0), 'TP_4': np.int64(0), 'TN_4': np.int64(92), 'FP_4': np.int64(0), 'FN_4': np.int64(40), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:12:56,016][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-32
-[2025-06-03 01:12:56,017][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-32/config.json
-[2025-06-03 01:12:56,924][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-32/model.safetensors
-[2025-06-03 01:12:59,476][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:12:59,477][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:12:59,478][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:12:59,478][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:12:59,693][transformers][INFO] - {'accuracy': 0.21212121212121213, 'RMSE': 45.79268169663901, 'QWK': 0.28539241457003384, 'HDIV': 0.0, 'Macro_F1': 0.08658585858585859, 'Micro_F1': 0.21212121212121213, 'Weighted_F1': 0.15464462809917356, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(108), 'FP_1': np.int64(0), 'FN_1': np.int64(24), 'TP_2': np.int64(5), 'TN_2': np.int64(71), 'FP_2': np.int64(55), 'FN_2': np.int64(1), 'TP_3': np.int64(23), 'TN_3': np.int64(30), 'FP_3': np.int64(49), 'FN_3': np.int64(30), 'TP_4': np.int64(0), 'TN_4': np.int64(92), 'FP_4': np.int64(0), 'FN_4': np.int64(40), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:12:59,696][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-64
-[2025-06-03 01:12:59,697][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-64/config.json
-[2025-06-03 01:13:00,623][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-64/model.safetensors
-[2025-06-03 01:13:01,336][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-32] due to args.save_total_limit
-[2025-06-03 01:13:03,238][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:13:03,240][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:13:03,240][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:13:03,240][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:13:03,455][transformers][INFO] - {'accuracy': 0.4696969696969697, 'RMSE': 45.52721463835969, 'QWK': 0.37069253931080626, 'HDIV': 0.06060606060606055, 'Macro_F1': 0.23939456241861742, 'Micro_F1': 0.4696969696969697, 'Weighted_F1': 0.4088047627566528, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(108), 'FP_1': np.int64(0), 'FN_1': np.int64(24), 'TP_2': np.int64(4), 'TN_2': np.int64(110), 'FP_2': np.int64(16), 'FN_2': np.int64(2), 'TP_3': np.int64(26), 'TN_3': np.int64(61), 'FP_3': np.int64(18), 'FN_3': np.int64(27), 'TP_4': np.int64(32), 'TN_4': np.int64(56), 'FP_4': np.int64(36), 'FN_4': np.int64(8), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:13:03,458][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-96
-[2025-06-03 01:13:03,459][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-96/config.json
-[2025-06-03 01:13:04,331][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-96/model.safetensors
-[2025-06-03 01:13:05,051][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-64] due to args.save_total_limit
-[2025-06-03 01:13:06,970][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:13:06,972][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:13:06,972][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:13:06,972][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:13:07,190][transformers][INFO] - {'accuracy': 0.4696969696969697, 'RMSE': 41.92345116490003, 'QWK': 0.39902034664657116, 'HDIV': 0.022727272727272707, 'Macro_F1': 0.23648966956053571, 'Micro_F1': 0.4696969696969697, 'Weighted_F1': 0.4096629529700396, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(108), 'FP_1': np.int64(0), 'FN_1': np.int64(24), 'TP_2': np.int64(4), 'TN_2': np.int64(110), 'FP_2': np.int64(16), 'FN_2': np.int64(2), 'TP_3': np.int64(38), 'TN_3': np.int64(43), 'FP_3': np.int64(36), 'FN_3': np.int64(15), 'TP_4': np.int64(20), 'TN_4': np.int64(74), 'FP_4': np.int64(18), 'FN_4': np.int64(20), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:13:07,193][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-128
-[2025-06-03 01:13:07,194][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-128/config.json
-[2025-06-03 01:13:08,105][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-128/model.safetensors
-[2025-06-03 01:13:08,787][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-96] due to args.save_total_limit
-[2025-06-03 01:13:10,707][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:13:10,709][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:13:10,709][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:13:10,709][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:13:10,927][transformers][INFO] - {'accuracy': 0.36363636363636365, 'RMSE': 44.17595671307132, 'QWK': 0.4778891509433961, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.20135414869760224, 'Micro_F1': 0.36363636363636365, 'Weighted_F1': 0.3738767701162043, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(7), 'TN_1': np.int64(95), 'FP_1': np.int64(13), 'FN_1': np.int64(17), 'TP_2': np.int64(0), 'TN_2': np.int64(102), 'FP_2': np.int64(24), 'FN_2': np.int64(6), 'TP_3': np.int64(28), 'TN_3': np.int64(41), 'FP_3': np.int64(38), 'FN_3': np.int64(25), 'TP_4': np.int64(13), 'TN_4': np.int64(83), 'FP_4': np.int64(9), 'FN_4': np.int64(27), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:13:10,930][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-160
-[2025-06-03 01:13:10,931][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-160/config.json
-[2025-06-03 01:13:11,783][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-160/model.safetensors
-[2025-06-03 01:13:12,475][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-128] due to args.save_total_limit
-[2025-06-03 01:13:14,386][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:13:14,388][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:13:14,388][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:13:14,388][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:13:14,605][transformers][INFO] - {'accuracy': 0.48484848484848486, 'RMSE': 45.52721463835969, 'QWK': 0.2555408970976253, 'HDIV': 0.037878787878787845, 'Macro_F1': 0.1874686297473649, 'Micro_F1': 0.48484848484848486, 'Weighted_F1': 0.3989510294512804, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(108), 'FP_1': np.int64(0), 'FN_1': np.int64(24), 'TP_2': np.int64(0), 'TN_2': np.int64(126), 'FP_2': np.int64(0), 'FN_2': np.int64(6), 'TP_3': np.int64(41), 'TN_3': np.int64(34), 'FP_3': np.int64(45), 'FN_3': np.int64(12), 'TP_4': np.int64(23), 'TN_4': np.int64(69), 'FP_4': np.int64(23), 'FN_4': np.int64(17), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:13:14,608][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-192
-[2025-06-03 01:13:14,609][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-192/config.json
-[2025-06-03 01:13:15,490][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-192/model.safetensors
-[2025-06-03 01:13:18,002][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:13:18,004][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:13:18,004][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:13:18,004][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:13:18,233][transformers][INFO] - {'accuracy': 0.5, 'RMSE': 44.17595671307132, 'QWK': 0.31053724370620295, 'HDIV': 0.030303030303030276, 'Macro_F1': 0.2636899384866865, 'Micro_F1': 0.5, 'Weighted_F1': 0.42740803309909, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(108), 'FP_1': np.int64(0), 'FN_1': np.int64(24), 'TP_2': np.int64(3), 'TN_2': np.int64(121), 'FP_2': np.int64(5), 'FN_2': np.int64(3), 'TP_3': np.int64(40), 'TN_3': np.int64(37), 'FP_3': np.int64(42), 'FN_3': np.int64(13), 'TP_4': np.int64(23), 'TN_4': np.int64(73), 'FP_4': np.int64(19), 'FN_4': np.int64(17), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:13:18,235][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-224
-[2025-06-03 01:13:18,236][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-224/config.json
-[2025-06-03 01:13:19,191][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-224/model.safetensors
-[2025-06-03 01:13:19,880][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-192] due to args.save_total_limit
-[2025-06-03 01:13:21,800][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:13:21,802][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:13:21,802][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:13:21,802][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:13:22,021][transformers][INFO] - {'accuracy': 0.4166666666666667, 'RMSE': 40.45199174779452, 'QWK': 0.47477010139118137, 'HDIV': 0.015151515151515138, 'Macro_F1': 0.2165132165132165, 'Micro_F1': 0.4166666666666667, 'Weighted_F1': 0.38379338379338374, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(108), 'FP_1': np.int64(0), 'FN_1': np.int64(24), 'TP_2': np.int64(5), 'TN_2': np.int64(95), 'FP_2': np.int64(31), 'FN_2': np.int64(1), 'TP_3': np.int64(29), 'TN_3': np.int64(50), 'FP_3': np.int64(29), 'FN_3': np.int64(24), 'TP_4': np.int64(21), 'TN_4': np.int64(75), 'FP_4': np.int64(17), 'FN_4': np.int64(19), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:13:22,024][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-256
-[2025-06-03 01:13:22,025][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-256/config.json
-[2025-06-03 01:13:22,811][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-256/model.safetensors
-[2025-06-03 01:13:23,519][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-224] due to args.save_total_limit
-[2025-06-03 01:13:25,457][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:13:25,459][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:13:25,459][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:13:25,459][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:13:25,682][transformers][INFO] - {'accuracy': 0.5227272727272727, 'RMSE': 44.44949466256704, 'QWK': 0.31442773387713485, 'HDIV': 0.037878787878787845, 'Macro_F1': 0.24489711251244609, 'Micro_F1': 0.5227272727272727, 'Weighted_F1': 0.441016956823462, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(108), 'FP_1': np.int64(0), 'FN_1': np.int64(24), 'TP_2': np.int64(1), 'TN_2': np.int64(125), 'FP_2': np.int64(1), 'FN_2': np.int64(5), 'TP_3': np.int64(40), 'TN_3': np.int64(41), 'FP_3': np.int64(38), 'FN_3': np.int64(13), 'TP_4': np.int64(28), 'TN_4': np.int64(68), 'FP_4': np.int64(24), 'FN_4': np.int64(12), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:13:25,684][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-288
-[2025-06-03 01:13:25,686][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-288/config.json
-[2025-06-03 01:13:26,502][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-288/model.safetensors
-[2025-06-03 01:13:27,281][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-256] due to args.save_total_limit
-[2025-06-03 01:13:29,227][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:13:29,229][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:13:29,229][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:13:29,229][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:13:29,447][transformers][INFO] - {'accuracy': 0.4166666666666667, 'RMSE': 41.92345116490003, 'QWK': 0.45729840081660433, 'HDIV': 0.030303030303030276, 'Macro_F1': 0.2168877602045919, 'Micro_F1': 0.4166666666666667, 'Weighted_F1': 0.38176869635015453, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(108), 'FP_1': np.int64(0), 'FN_1': np.int64(24), 'TP_2': np.int64(5), 'TN_2': np.int64(95), 'FP_2': np.int64(31), 'FN_2': np.int64(1), 'TP_3': np.int64(25), 'TN_3': np.int64(56), 'FP_3': np.int64(23), 'FN_3': np.int64(28), 'TP_4': np.int64(25), 'TN_4': np.int64(69), 'FP_4': np.int64(23), 'FN_4': np.int64(15), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:13:29,450][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-320
-[2025-06-03 01:13:29,451][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-320/config.json
-[2025-06-03 01:13:30,372][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-320/model.safetensors
-[2025-06-03 01:13:31,121][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-288] due to args.save_total_limit
-[2025-06-03 01:13:31,200][transformers.trainer][INFO] - 
-
-Training completed. Do not forget to share your model on huggingface.co/models =)
-
-
-[2025-06-03 01:13:31,200][transformers.trainer][INFO] - Loading best model from /workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-160 (score: 0.4778891509433961).
-[2025-06-03 01:13:31,320][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-12-43/results/checkpoint-320] due to args.save_total_limit
-[2025-06-03 01:13:31,404][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:13:31,406][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:13:31,406][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:13:31,406][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:13:31,645][transformers][INFO] - {'accuracy': 0.36363636363636365, 'RMSE': 44.17595671307132, 'QWK': 0.4778891509433961, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.20135414869760224, 'Micro_F1': 0.36363636363636365, 'Weighted_F1': 0.3738767701162043, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(7), 'TN_1': np.int64(95), 'FP_1': np.int64(13), 'FN_1': np.int64(17), 'TP_2': np.int64(0), 'TN_2': np.int64(102), 'FP_2': np.int64(24), 'FN_2': np.int64(6), 'TP_3': np.int64(28), 'TN_3': np.int64(41), 'FP_3': np.int64(38), 'FN_3': np.int64(25), 'TP_4': np.int64(13), 'TN_4': np.int64(83), 'FP_4': np.int64(9), 'FN_4': np.int64(27), 'TP_5': np.int64(0), 'TN_5': np.int64(124), 'FP_5': np.int64(0), 'FN_5': np.int64(8)}
-[2025-06-03 01:13:31,649][__main__][INFO] - Training completed successfully.
-[2025-06-03 01:13:31,649][__main__][INFO] - Running on Test
-[2025-06-03 01:13:31,649][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference. If grades, supporting_text, id_prompt, essay_text, essay_year, id, prompt, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:13:31,650][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:13:31,650][transformers.trainer][INFO] -   Num examples = 138
-[2025-06-03 01:13:31,651][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:13:31,880][transformers][INFO] - {'accuracy': 0.2608695652173913, 'RMSE': 52.1980620440972, 'QWK': 0.33263365847635495, 'HDIV': 0.036231884057971064, 'Macro_F1': 0.16607083828156566, 'Micro_F1': 0.2608695652173913, 'Weighted_F1': 0.25270416127040973, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(8), 'TN_1': np.int64(85), 'FP_1': np.int64(24), 'FN_1': np.int64(21), 'TP_2': np.int64(4), 'TN_2': np.int64(90), 'FP_2': np.int64(30), 'FN_2': np.int64(14), 'TP_3': np.int64(18), 'TN_3': np.int64(53), 'FP_3': np.int64(40), 'FN_3': np.int64(27), 'TP_4': np.int64(6), 'TN_4': np.int64(92), 'FP_4': np.int64(8), 'FN_4': np.int64(32), 'TP_5': np.int64(0), 'TN_5': np.int64(131), 'FP_5': np.int64(0), 'FN_5': np.int64(7)}
-[2025-06-03 01:13:31,883][transformers.trainer][INFO] - Saving model checkpoint to ./results/best_model
-[2025-06-03 01:13:31,884][transformers.configuration_utils][INFO] - Configuration saved in ./results/best_model/config.json
-[2025-06-03 01:13:32,915][transformers.modeling_utils][INFO] - Model weights saved in ./results/best_model/model.safetensors
-[2025-06-03 01:13:32,917][transformers.tokenization_utils_base][INFO] - tokenizer config file saved in ./results/best_model/tokenizer_config.json
-[2025-06-03 01:13:32,917][transformers.tokenization_utils_base][INFO] - Special tokens file saved in ./results/best_model/special_tokens_map.json
-[2025-06-03 01:13:32,926][__main__][INFO] - Model and tokenizer saved to ./results/best_model
-[2025-06-03 01:13:32,928][__main__][INFO] - Fine Tuning Finished.
-[2025-06-03 01:13:33,439][__main__][INFO] - Total emissions: 0.0003 kg CO2eq
+version https://git-lfs.github.com/spec/v1
+oid sha256:a3735016e5562be3bcdf61daaf7b9100d3754a6c4269d18fe835cce696c45a4d
+size 38196

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C4/emissions.csv

@@ -1,2 +1,3 @@
-timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
-2025-06-03T01:17:02,jbcs2025,4925de49-550a-4b4a-994c-821f3b4d097b,bert-base-portuguese-cased-encoder_ordinal_coral-C4,83.9635311360471,0.00048460052865986135,5.771559653376862e-06,86.50833333333333,224.1647263048748,70.0,0.0017773572962485446,0.00526824254791336,0.0016019586179780569,0.008647558462139961,France,FRA,île-de-france,,,Linux-5.15.0-136-generic-x86_64-with-glibc2.35,3.12.10,3.0.2,192,INTEL(R) XEON(R) PLATINUM 8568Y+,1,1 x NVIDIA H200,2.3494,48.8558,2015.3635139465332,machine,N,1.0
+version https://git-lfs.github.com/spec/v1
+oid sha256:8d3cc7dcdbdbed55c6fe11e42d562b6d032273dd2051b0af7acbc54fa244b7e4
+size 858

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C4/evaluation_results.csv

@@ -1,4 +1,3 @@
-eval_loss,eval_model_preparation_time,eval_accuracy,eval_RMSE,eval_QWK,eval_HDIV,eval_Macro_F1,eval_Micro_F1,eval_Weighted_F1,eval_TP_0,eval_TN_0,eval_FP_0,eval_FN_0,eval_TP_1,eval_TN_1,eval_FP_1,eval_FN_1,eval_TP_2,eval_TN_2,eval_FP_2,eval_FN_2,eval_TP_3,eval_TN_3,eval_FP_3,eval_FN_3,eval_TP_4,eval_TN_4,eval_FP_4,eval_FN_4,eval_TP_5,eval_TN_5,eval_FP_5,eval_FN_5,eval_runtime,eval_samples_per_second,eval_steps_per_second,epoch,reference,timestamp,id
-31.721242904663086,0.0015,0.17424242424242425,73.69058983549412,-0.007942730526674602,0.18939393939393945,0.07632561613144137,0.17424242424242425,0.20805214203272454,0,131,0,1,0,100,32,0,1,68,60,3,22,51,17,42,0,84,0,48,0,117,0,15,0.5952,221.767,15.12,-1,validation_before_training,2025-06-03 01:15:44,bert-base-portuguese-cased-encoder_ordinal_coral-C4
-8.436115264892578,0.0015,0.5681818181818182,30.550504633038933,0.4841656516443361,0.007575757575757569,0.31708817498291186,0.5681818181818182,0.5635369415273722,0,131,0,1,0,132,0,0,0,128,0,4,36,56,12,28,33,51,33,15,6,105,12,9,0.2331,566.185,38.603,20.0,validation_after_training,2025-06-03 01:15:44,bert-base-portuguese-cased-encoder_ordinal_coral-C4
-7.2303924560546875,0.0015,0.644927536231884,26.37521893583148,0.5818181818181818,0.007246376811594235,0.35879198887141794,0.644927536231884,0.643663118795876,0,137,0,1,0,137,0,1,3,124,5,6,53,45,17,23,30,70,22,16,3,128,5,2,0.2196,628.314,40.977,20.0,test_results,2025-06-03 01:15:44,bert-base-portuguese-cased-encoder_ordinal_coral-C4
+version https://git-lfs.github.com/spec/v1
+oid sha256:0a338d51dcd946f3e0c86113b053762f44dc786432915105562e092025a58abd
+size 1496

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C4/results/best_model/config.json

@@ -1,45 +1,3 @@
-{
-  "architectures": [
-    "BertForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cf1f6d6785c3b5bcfc91fad895c1ed8a279abdc99a665ea0767faf219a6e2d9
+size 1047

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C4/results/best_model/special_tokens_map.json

@@ -1,7 +1,3 @@
-{
-  "cls_token": "[CLS]",
-  "mask_token": "[MASK]",
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "unk_token": "[UNK]"
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6d346be366a7d1d48332dbc9fdf3bf8960b5d879522b7799ddba59e76237ee3
+size 125

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C4/results/best_model/tokenizer_config.json

@@ -1,58 +1,3 @@
-{
-  "added_tokens_decoder": {
-    "0": {
-      "content": "[PAD]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "100": {
-      "content": "[UNK]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "101": {
-      "content": "[CLS]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "102": {
-      "content": "[SEP]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "103": {
-      "content": "[MASK]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    }
-  },
-  "clean_up_tokenization_spaces": true,
-  "cls_token": "[CLS]",
-  "do_basic_tokenize": true,
-  "do_lower_case": false,
-  "extra_special_tokens": {},
-  "mask_token": "[MASK]",
-  "model_max_length": 1000000000000000019884624838656,
-  "never_split": null,
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "strip_accents": null,
-  "tokenize_chinese_chars": true,
-  "tokenizer_class": "BertTokenizer",
-  "unk_token": "[UNK]"
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ab044e4a71cdb2a5cff548e16d3bcd46a757848ef861743426c44a134b00da1
+size 1301

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C4/results/checkpoint-480/config.json

@@ -1,45 +1,3 @@
-{
-  "architectures": [
-    "BertForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cf1f6d6785c3b5bcfc91fad895c1ed8a279abdc99a665ea0767faf219a6e2d9
+size 1047

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C4/results/checkpoint-480/trainer_state.json

@@ -1,671 +1,3 @@
-{
-  "best_global_step": 480,
-  "best_metric": 0.4841656516443361,
-  "best_model_checkpoint": "/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-480",
-  "epoch": 15.0,
-  "eval_steps": 500,
-  "global_step": 480,
-  "is_hyper_param_search": false,
-  "is_local_process_zero": true,
-  "is_world_process_zero": true,
-  "log_history": [
-    {
-      "epoch": 1.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 0,
-      "eval_FN_4": 48,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 68,
-      "eval_FP_4": 0,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.13061224489795917,
-      "eval_Micro_F1": 0.48484848484848486,
-      "eval_QWK": 0.0,
-      "eval_RMSE": 38.297084310253524,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 0,
-      "eval_TN_4": 84,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 64,
-      "eval_TP_4": 0,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.31663574520717375,
-      "eval_accuracy": 0.48484848484848486,
-      "eval_loss": 12.534611701965332,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2167,
-      "eval_samples_per_second": 609.065,
-      "eval_steps_per_second": 41.527,
-      "step": 32
-    },
-    {
-      "epoch": 2.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 16,
-      "eval_FN_4": 16,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 24,
-      "eval_FP_4": 28,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.2596949891067538,
-      "eval_Micro_F1": 0.6060606060606061,
-      "eval_QWK": 0.40749414519906313,
-      "eval_RMSE": 28.91995221924885,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 44,
-      "eval_TN_4": 56,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 48,
-      "eval_TP_4": 32,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.5577342047930283,
-      "eval_accuracy": 0.6060606060606061,
-      "eval_loss": 8.368426322937012,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2269,
-      "eval_samples_per_second": 581.713,
-      "eval_steps_per_second": 39.662,
-      "step": 64
-    },
-    {
-      "epoch": 3.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 39,
-      "eval_FN_4": 4,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 7,
-      "eval_FP_4": 56,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.2230855855855856,
-      "eval_Micro_F1": 0.5227272727272727,
-      "eval_QWK": 0.3211327811915575,
-      "eval_RMSE": 30.550504633038933,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 61,
-      "eval_TN_4": 28,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 25,
-      "eval_TP_4": 44,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.46874146874146877,
-      "eval_accuracy": 0.5227272727272727,
-      "eval_loss": 7.869194030761719,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2156,
-      "eval_samples_per_second": 612.315,
-      "eval_steps_per_second": 41.749,
-      "step": 96
-    },
-    {
-      "epoch": 3.125,
-      "grad_norm": 26.696069717407227,
-      "learning_rate": 4.696180555555556e-05,
-      "loss": 13.6866,
-      "step": 100
-    },
-    {
-      "epoch": 4.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 25,
-      "eval_FN_4": 6,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 13,
-      "eval_FP_4": 38,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.2657327586206897,
-      "eval_Micro_F1": 0.6136363636363636,
-      "eval_QWK": 0.43448457685209596,
-      "eval_RMSE": 28.06917861068948,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 55,
-      "eval_TN_4": 46,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 39,
-      "eval_TP_4": 42,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.5646551724137931,
-      "eval_accuracy": 0.6136363636363636,
-      "eval_loss": 6.886540412902832,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2166,
-      "eval_samples_per_second": 609.404,
-      "eval_steps_per_second": 41.55,
-      "step": 128
-    },
-    {
-      "epoch": 5.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 30,
-      "eval_FN_4": 6,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 12,
-      "eval_FP_4": 44,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.24900949796472185,
-      "eval_Micro_F1": 0.5757575757575758,
-      "eval_QWK": 0.414769719428269,
-      "eval_RMSE": 28.4977404739606,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 56,
-      "eval_TN_4": 40,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 34,
-      "eval_TP_4": 42,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.5276756712306236,
-      "eval_accuracy": 0.5757575757575758,
-      "eval_loss": 7.428503036499023,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2166,
-      "eval_samples_per_second": 609.552,
-      "eval_steps_per_second": 41.56,
-      "step": 160
-    },
-    {
-      "epoch": 6.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 38,
-      "eval_FN_4": 5,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 8,
-      "eval_FP_4": 55,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.22393066815767404,
-      "eval_Micro_F1": 0.5227272727272727,
-      "eval_QWK": 0.32203842049092846,
-      "eval_RMSE": 30.550504633038933,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 60,
-      "eval_TN_4": 29,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 26,
-      "eval_TP_4": 43,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.47146330512279633,
-      "eval_accuracy": 0.5227272727272727,
-      "eval_loss": 8.33031940460205,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2169,
-      "eval_samples_per_second": 608.44,
-      "eval_steps_per_second": 41.485,
-      "step": 192
-    },
-    {
-      "epoch": 6.25,
-      "grad_norm": 46.046146392822266,
-      "learning_rate": 3.828125e-05,
-      "loss": 5.6219,
-      "step": 200
-    },
-    {
-      "epoch": 7.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 22,
-      "eval_FN_4": 12,
-      "eval_FN_5": 14,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 18,
-      "eval_FP_4": 34,
-      "eval_FP_5": 1,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.28104718103753257,
-      "eval_Micro_F1": 0.5984848484848485,
-      "eval_QWK": 0.43883248730964475,
-      "eval_RMSE": 28.4977404739606,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 50,
-      "eval_TN_4": 50,
-      "eval_TN_5": 116,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 42,
-      "eval_TP_4": 36,
-      "eval_TP_5": 1,
-      "eval_Weighted_F1": 0.5636945468579598,
-      "eval_accuracy": 0.5984848484848485,
-      "eval_loss": 7.343842506408691,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2293,
-      "eval_samples_per_second": 575.604,
-      "eval_steps_per_second": 39.246,
-      "step": 224
-    },
-    {
-      "epoch": 8.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 34,
-      "eval_FN_4": 6,
-      "eval_FN_5": 14,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 10,
-      "eval_FP_4": 48,
-      "eval_FP_5": 1,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.2606531575841039,
-      "eval_Micro_F1": 0.553030303030303,
-      "eval_QWK": 0.4316195372750643,
-      "eval_RMSE": 28.4977404739606,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 58,
-      "eval_TN_4": 36,
-      "eval_TN_5": 116,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 30,
-      "eval_TP_4": 42,
-      "eval_TP_5": 1,
-      "eval_Weighted_F1": 0.5144331371952855,
-      "eval_accuracy": 0.553030303030303,
-      "eval_loss": 7.712894916534424,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2174,
-      "eval_samples_per_second": 607.191,
-      "eval_steps_per_second": 41.399,
-      "step": 256
-    },
-    {
-      "epoch": 9.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 23,
-      "eval_FN_4": 12,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 19,
-      "eval_FP_4": 36,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.25225806451612903,
-      "eval_Micro_F1": 0.5833333333333334,
-      "eval_QWK": 0.4028324154209283,
-      "eval_RMSE": 28.91995221924885,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 49,
-      "eval_TN_4": 48,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 41,
-      "eval_TP_4": 36,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.5388074291300098,
-      "eval_accuracy": 0.5833333333333334,
-      "eval_loss": 7.401371002197266,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2162,
-      "eval_samples_per_second": 610.585,
-      "eval_steps_per_second": 41.631,
-      "step": 288
-    },
-    {
-      "epoch": 9.375,
-      "grad_norm": 23.822612762451172,
-      "learning_rate": 2.9600694444444445e-05,
-      "loss": 4.6489,
-      "step": 300
-    },
-    {
-      "epoch": 10.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 3,
-      "eval_FN_3": 26,
-      "eval_FN_4": 19,
-      "eval_FN_5": 11,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 3,
-      "eval_FP_3": 18,
-      "eval_FP_4": 29,
-      "eval_FP_5": 10,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.3412730427239211,
-      "eval_Micro_F1": 0.5454545454545454,
-      "eval_QWK": 0.44955787781350476,
-      "eval_RMSE": 31.71845844395036,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 125,
-      "eval_TN_3": 50,
-      "eval_TN_4": 55,
-      "eval_TN_5": 107,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 1,
-      "eval_TP_3": 38,
-      "eval_TP_4": 29,
-      "eval_TP_5": 4,
-      "eval_Weighted_F1": 0.5449652675091843,
-      "eval_accuracy": 0.5454545454545454,
-      "eval_loss": 8.140850067138672,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2156,
-      "eval_samples_per_second": 612.23,
-      "eval_steps_per_second": 41.743,
-      "step": 320
-    },
-    {
-      "epoch": 11.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 34,
-      "eval_FN_4": 5,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 10,
-      "eval_FP_4": 49,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.23824175824175825,
-      "eval_Micro_F1": 0.553030303030303,
-      "eval_QWK": 0.4124368854637257,
-      "eval_RMSE": 28.4977404739606,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 58,
-      "eval_TN_4": 35,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 30,
-      "eval_TP_4": 43,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.503096903096903,
-      "eval_accuracy": 0.553030303030303,
-      "eval_loss": 8.11368465423584,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2162,
-      "eval_samples_per_second": 610.592,
-      "eval_steps_per_second": 41.631,
-      "step": 352
-    },
-    {
-      "epoch": 12.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 33,
-      "eval_FN_4": 5,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 9,
-      "eval_FP_4": 49,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.2420879120879121,
-      "eval_Micro_F1": 0.5606060606060606,
-      "eval_QWK": 0.3948976880148818,
-      "eval_RMSE": 28.91995221924885,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 59,
-      "eval_TN_4": 35,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 31,
-      "eval_TP_4": 43,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.5124209124209125,
-      "eval_accuracy": 0.5606060606060606,
-      "eval_loss": 7.897758483886719,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2165,
-      "eval_samples_per_second": 609.763,
-      "eval_steps_per_second": 41.575,
-      "step": 384
-    },
-    {
-      "epoch": 12.5,
-      "grad_norm": 44.878665924072266,
-      "learning_rate": 2.092013888888889e-05,
-      "loss": 4.1866,
-      "step": 400
-    },
-    {
-      "epoch": 13.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 32,
-      "eval_FN_4": 5,
-      "eval_FN_5": 15,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 10,
-      "eval_FP_4": 47,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.24539239814055236,
-      "eval_Micro_F1": 0.5681818181818182,
-      "eval_QWK": 0.43073248407643305,
-      "eval_RMSE": 28.06917861068948,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 58,
-      "eval_TN_4": 37,
-      "eval_TN_5": 117,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 32,
-      "eval_TP_4": 43,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.519352673577448,
-      "eval_accuracy": 0.5681818181818182,
-      "eval_loss": 8.067130088806152,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2172,
-      "eval_samples_per_second": 607.827,
-      "eval_steps_per_second": 41.443,
-      "step": 416
-    },
-    {
-      "epoch": 14.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 31,
-      "eval_FN_4": 9,
-      "eval_FN_5": 13,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 11,
-      "eval_FP_4": 41,
-      "eval_FP_5": 6,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.2788798309178744,
-      "eval_Micro_F1": 0.5606060606060606,
-      "eval_QWK": 0.4218640504555011,
-      "eval_RMSE": 30.15113445777636,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 57,
-      "eval_TN_4": 43,
-      "eval_TN_5": 111,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 33,
-      "eval_TP_4": 39,
-      "eval_TP_5": 2,
-      "eval_Weighted_F1": 0.5376500512370077,
-      "eval_accuracy": 0.5606060606060606,
-      "eval_loss": 8.414743423461914,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2151,
-      "eval_samples_per_second": 613.555,
-      "eval_steps_per_second": 41.833,
-      "step": 448
-    },
-    {
-      "epoch": 15.0,
-      "eval_FN_0": 1,
-      "eval_FN_1": 0,
-      "eval_FN_2": 4,
-      "eval_FN_3": 28,
-      "eval_FN_4": 15,
-      "eval_FN_5": 9,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 0,
-      "eval_FP_3": 12,
-      "eval_FP_4": 33,
-      "eval_FP_5": 12,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.31708817498291186,
-      "eval_Micro_F1": 0.5681818181818182,
-      "eval_QWK": 0.4841656516443361,
-      "eval_RMSE": 30.550504633038933,
-      "eval_TN_0": 131,
-      "eval_TN_1": 132,
-      "eval_TN_2": 128,
-      "eval_TN_3": 56,
-      "eval_TN_4": 51,
-      "eval_TN_5": 105,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 0,
-      "eval_TP_3": 36,
-      "eval_TP_4": 33,
-      "eval_TP_5": 6,
-      "eval_Weighted_F1": 0.5635369415273722,
-      "eval_accuracy": 0.5681818181818182,
-      "eval_loss": 8.436115264892578,
-      "eval_model_preparation_time": 0.0015,
-      "eval_runtime": 0.2305,
-      "eval_samples_per_second": 572.743,
-      "eval_steps_per_second": 39.051,
-      "step": 480
-    }
-  ],
-  "logging_steps": 100,
-  "max_steps": 640,
-  "num_input_tokens_seen": 0,
-  "num_train_epochs": 20,
-  "save_steps": 500,
-  "stateful_callbacks": {
-    "EarlyStoppingCallback": {
-      "args": {
-        "early_stopping_patience": 5,
-        "early_stopping_threshold": 0.0
-      },
-      "attributes": {
-        "early_stopping_patience_counter": 0
-      }
-    },
-    "TrainerControl": {
-      "args": {
-        "should_epoch_stop": false,
-        "should_evaluate": false,
-        "should_log": false,
-        "should_save": true,
-        "should_training_stop": false
-      },
-      "attributes": {}
-    }
-  },
-  "total_flos": 1973386068480000.0,
-  "train_batch_size": 16,
-  "trial_name": null,
-  "trial_params": null
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:c6938ab2f54cb1b2e3b124f44142427a379545f7ed52f3d3151a7651de4c5dbc
+size 17912

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C4/run_experiment.log

@@ -1,440 +1,3 @@
-[2025-06-03 01:15:35,311][__main__][INFO] - cache_dir: /tmp/
-dataset:
-  name: kamel-usp/aes_enem_dataset
-  split: JBCS2025
-training_params:
-  seed: 42
-  num_train_epochs: 20
-  logging_steps: 100
-  metric_for_best_model: QWK
-  bf16: true
-post_training_results:
-  model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
-experiments:
-  model:
-    name: neuralmind/bert-base-portuguese-cased
-    type: encoder_ordinal_coral
-    num_labels: 6
-    output_dir: ./results/
-    logging_dir: ./logs/
-    best_model_dir: ./results/best_model
-  tokenizer:
-    name: neuralmind/bert-base-portuguese-cased
-  dataset:
-    grade_index: 3
-  training_params:
-    weight_decay: 0.01
-    warmup_ratio: 0.1
-    learning_rate: 5.0e-05
-    train_batch_size: 16
-    eval_batch_size: 16
-    gradient_accumulation_steps: 1
-    gradient_checkpointing: false
-
-[2025-06-03 01:15:39,181][__main__][INFO] - GPU 0: NVIDIA H200 | TDP ≈ 700 W
-[2025-06-03 01:15:39,182][__main__][INFO] - Starting the Fine Tuning training process.
-[2025-06-03 01:15:42,969][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 01:15:42,970][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 01:15:43,128][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
-[2025-06-03 01:15:43,128][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
-[2025-06-03 01:15:43,129][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
-[2025-06-03 01:15:43,129][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
-[2025-06-03 01:15:43,129][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
-[2025-06-03 01:15:43,129][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
-[2025-06-03 01:15:43,129][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 01:15:43,129][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 01:15:43,152][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 01:15:43,152][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 01:15:43,166][__main__][INFO] - Tokenizer function parameters- Padding:max_length; Truncation: True
-[2025-06-03 01:15:43,497][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-03 01:15:43,497][transformers.configuration_utils][INFO] - Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
-
-[2025-06-03 01:15:43,920][transformers.modeling_utils][INFO] - loading weights file pytorch_model.bin from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/pytorch_model.bin
-[2025-06-03 01:15:44,030][transformers.modeling_utils][INFO] - Since the `torch_dtype` attribute can't be found in model's config object, will use torch_dtype={torch_dtype} as derived from model's weights
-[2025-06-03 01:15:44,030][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
-[2025-06-03 01:15:44,229][transformers.safetensors_conversion][INFO] - Attempting to create safetensors variant
-[2025-06-03 01:15:44,712][transformers.modeling_utils][INFO] - Some weights of the model checkpoint at neuralmind/bert-base-portuguese-cased were not used when initializing BertForSequenceClassification: ['cls.predictions.bias', 'cls.predictions.decoder.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.dense.weight', 'cls.seq_relationship.bias', 'cls.seq_relationship.weight']
-- This IS expected if you are initializing BertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
-- This IS NOT expected if you are initializing BertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
-[2025-06-03 01:15:44,712][transformers.modeling_utils][WARNING] - Some weights of BertForSequenceClassification were not initialized from the model checkpoint at neuralmind/bert-base-portuguese-cased and are newly initialized: ['classifier.bias', 'classifier.weight']
-You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
-[2025-06-03 01:15:44,716][transformers.training_args][INFO] - PyTorch: setting up devices
-[2025-06-03 01:15:44,751][__main__][INFO] - Total steps: 620. Number of warmup steps: 62
-[2025-06-03 01:15:44,756][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
-[2025-06-03 01:15:44,774][transformers.trainer][INFO] - Using auto half precision backend
-[2025-06-03 01:15:44,776][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:15:44,780][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:15:44,780][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:15:44,780][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:15:44,940][transformers.safetensors_conversion][INFO] - Safetensors PR exists
-[2025-06-03 01:15:45,374][transformers][INFO] - {'accuracy': 0.17424242424242425, 'RMSE': 73.69058983549412, 'QWK': -0.007942730526674602, 'HDIV': 0.18939393939393945, 'Macro_F1': 0.07632561613144137, 'Micro_F1': 0.17424242424242425, 'Weighted_F1': 0.20805214203272454, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(100), 'FP_1': np.int64(32), 'FN_1': np.int64(0), 'TP_2': np.int64(1), 'TN_2': np.int64(68), 'FP_2': np.int64(60), 'FN_2': np.int64(3), 'TP_3': np.int64(22), 'TN_3': np.int64(51), 'FP_3': np.int64(17), 'FN_3': np.int64(42), 'TP_4': np.int64(0), 'TN_4': np.int64(84), 'FP_4': np.int64(0), 'FN_4': np.int64(48), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 01:15:45,586][transformers.trainer][INFO] - The following columns in the Training set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:15:45,592][transformers.trainer][INFO] - ***** Running training *****
-[2025-06-03 01:15:45,592][transformers.trainer][INFO] -   Num examples = 500
-[2025-06-03 01:15:45,592][transformers.trainer][INFO] -   Num Epochs = 20
-[2025-06-03 01:15:45,592][transformers.trainer][INFO] -   Instantaneous batch size per device = 16
-[2025-06-03 01:15:45,592][transformers.trainer][INFO] -   Total train batch size (w. parallel, distributed & accumulation) = 16
-[2025-06-03 01:15:45,593][transformers.trainer][INFO] -   Gradient Accumulation steps = 1
-[2025-06-03 01:15:45,593][transformers.trainer][INFO] -   Total optimization steps = 640
-[2025-06-03 01:15:45,593][transformers.trainer][INFO] -   Number of trainable parameters = 108,926,981
-[2025-06-03 01:15:47,629][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:15:47,631][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:15:47,631][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:15:47,631][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:15:47,848][transformers][INFO] - {'accuracy': 0.48484848484848486, 'RMSE': 38.297084310253524, 'QWK': 0.0, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.13061224489795917, 'Micro_F1': 0.48484848484848486, 'Weighted_F1': 0.31663574520717375, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(64), 'TN_3': np.int64(0), 'FP_3': np.int64(68), 'FN_3': np.int64(0), 'TP_4': np.int64(0), 'TN_4': np.int64(84), 'FP_4': np.int64(0), 'FN_4': np.int64(48), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 01:15:47,851][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-32
-[2025-06-03 01:15:47,852][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-32/config.json
-[2025-06-03 01:15:48,690][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-32/model.safetensors
-[2025-06-03 01:15:51,194][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:15:51,198][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:15:51,198][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:15:51,198][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:15:51,425][transformers][INFO] - {'accuracy': 0.6060606060606061, 'RMSE': 28.91995221924885, 'QWK': 0.40749414519906313, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2596949891067538, 'Micro_F1': 0.6060606060606061, 'Weighted_F1': 0.5577342047930283, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(48), 'TN_3': np.int64(44), 'FP_3': np.int64(24), 'FN_3': np.int64(16), 'TP_4': np.int64(32), 'TN_4': np.int64(56), 'FP_4': np.int64(28), 'FN_4': np.int64(16), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 01:15:51,428][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-64
-[2025-06-03 01:15:51,429][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-64/config.json
-[2025-06-03 01:15:52,211][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-64/model.safetensors
-[2025-06-03 01:15:52,886][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-32] due to args.save_total_limit
-[2025-06-03 01:15:54,783][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:15:54,785][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:15:54,785][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:15:54,785][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:15:55,002][transformers][INFO] - {'accuracy': 0.5227272727272727, 'RMSE': 30.550504633038933, 'QWK': 0.3211327811915575, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2230855855855856, 'Micro_F1': 0.5227272727272727, 'Weighted_F1': 0.46874146874146877, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(25), 'TN_3': np.int64(61), 'FP_3': np.int64(7), 'FN_3': np.int64(39), 'TP_4': np.int64(44), 'TN_4': np.int64(28), 'FP_4': np.int64(56), 'FN_4': np.int64(4), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 01:15:55,004][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-96
-[2025-06-03 01:15:55,005][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-96/config.json
-[2025-06-03 01:15:55,901][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-96/model.safetensors
-[2025-06-03 01:15:58,421][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:15:58,423][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:15:58,423][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:15:58,423][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:15:58,640][transformers][INFO] - {'accuracy': 0.6136363636363636, 'RMSE': 28.06917861068948, 'QWK': 0.43448457685209596, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2657327586206897, 'Micro_F1': 0.6136363636363636, 'Weighted_F1': 0.5646551724137931, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(39), 'TN_3': np.int64(55), 'FP_3': np.int64(13), 'FN_3': np.int64(25), 'TP_4': np.int64(42), 'TN_4': np.int64(46), 'FP_4': np.int64(38), 'FN_4': np.int64(6), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 01:15:58,643][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-128
-[2025-06-03 01:15:58,644][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-128/config.json
-[2025-06-03 01:15:59,519][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-128/model.safetensors
-[2025-06-03 01:16:00,225][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-64] due to args.save_total_limit
-[2025-06-03 01:16:00,298][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-96] due to args.save_total_limit
-[2025-06-03 01:16:02,210][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:02,212][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:02,212][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:02,212][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:02,429][transformers][INFO] - {'accuracy': 0.5757575757575758, 'RMSE': 28.4977404739606, 'QWK': 0.414769719428269, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.24900949796472185, 'Micro_F1': 0.5757575757575758, 'Weighted_F1': 0.5276756712306236, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(34), 'TN_3': np.int64(56), 'FP_3': np.int64(12), 'FN_3': np.int64(30), 'TP_4': np.int64(42), 'TN_4': np.int64(40), 'FP_4': np.int64(44), 'FN_4': np.int64(6), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 01:16:02,432][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-160
-[2025-06-03 01:16:02,433][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-160/config.json
-[2025-06-03 01:16:03,209][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-160/model.safetensors
-[2025-06-03 01:16:05,741][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:05,743][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:05,743][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:05,743][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:05,961][transformers][INFO] - {'accuracy': 0.5227272727272727, 'RMSE': 30.550504633038933, 'QWK': 0.32203842049092846, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.22393066815767404, 'Micro_F1': 0.5227272727272727, 'Weighted_F1': 0.47146330512279633, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(26), 'TN_3': np.int64(60), 'FP_3': np.int64(8), 'FN_3': np.int64(38), 'TP_4': np.int64(43), 'TN_4': np.int64(29), 'FP_4': np.int64(55), 'FN_4': np.int64(5), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 01:16:05,964][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-192
-[2025-06-03 01:16:05,965][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-192/config.json
-[2025-06-03 01:16:06,878][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-192/model.safetensors
-[2025-06-03 01:16:07,559][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-160] due to args.save_total_limit
-[2025-06-03 01:16:09,465][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:09,467][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:09,467][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:09,467][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:09,697][transformers][INFO] - {'accuracy': 0.5984848484848485, 'RMSE': 28.4977404739606, 'QWK': 0.43883248730964475, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.28104718103753257, 'Micro_F1': 0.5984848484848485, 'Weighted_F1': 0.5636945468579598, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(42), 'TN_3': np.int64(50), 'FP_3': np.int64(18), 'FN_3': np.int64(22), 'TP_4': np.int64(36), 'TN_4': np.int64(50), 'FP_4': np.int64(34), 'FN_4': np.int64(12), 'TP_5': np.int64(1), 'TN_5': np.int64(116), 'FP_5': np.int64(1), 'FN_5': np.int64(14)}
-[2025-06-03 01:16:09,700][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-224
-[2025-06-03 01:16:09,701][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-224/config.json
-[2025-06-03 01:16:10,587][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-224/model.safetensors
-[2025-06-03 01:16:11,272][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-128] due to args.save_total_limit
-[2025-06-03 01:16:11,341][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-192] due to args.save_total_limit
-[2025-06-03 01:16:13,245][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:13,247][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:13,247][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:13,247][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:13,465][transformers][INFO] - {'accuracy': 0.553030303030303, 'RMSE': 28.4977404739606, 'QWK': 0.4316195372750643, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2606531575841039, 'Micro_F1': 0.553030303030303, 'Weighted_F1': 0.5144331371952855, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(30), 'TN_3': np.int64(58), 'FP_3': np.int64(10), 'FN_3': np.int64(34), 'TP_4': np.int64(42), 'TN_4': np.int64(36), 'FP_4': np.int64(48), 'FN_4': np.int64(6), 'TP_5': np.int64(1), 'TN_5': np.int64(116), 'FP_5': np.int64(1), 'FN_5': np.int64(14)}
-[2025-06-03 01:16:13,469][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-256
-[2025-06-03 01:16:13,470][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-256/config.json
-[2025-06-03 01:16:14,395][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-256/model.safetensors
-[2025-06-03 01:16:16,946][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:16,948][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:16,948][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:16,948][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:17,165][transformers][INFO] - {'accuracy': 0.5833333333333334, 'RMSE': 28.91995221924885, 'QWK': 0.4028324154209283, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.25225806451612903, 'Micro_F1': 0.5833333333333334, 'Weighted_F1': 0.5388074291300098, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(41), 'TN_3': np.int64(49), 'FP_3': np.int64(19), 'FN_3': np.int64(23), 'TP_4': np.int64(36), 'TN_4': np.int64(48), 'FP_4': np.int64(36), 'FN_4': np.int64(12), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 01:16:17,167][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-288
-[2025-06-03 01:16:17,169][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-288/config.json
-[2025-06-03 01:16:18,107][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-288/model.safetensors
-[2025-06-03 01:16:18,816][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-256] due to args.save_total_limit
-[2025-06-03 01:16:20,719][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:20,720][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:20,720][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:20,720][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:20,937][transformers][INFO] - {'accuracy': 0.5454545454545454, 'RMSE': 31.71845844395036, 'QWK': 0.44955787781350476, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.3412730427239211, 'Micro_F1': 0.5454545454545454, 'Weighted_F1': 0.5449652675091843, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(1), 'TN_2': np.int64(125), 'FP_2': np.int64(3), 'FN_2': np.int64(3), 'TP_3': np.int64(38), 'TN_3': np.int64(50), 'FP_3': np.int64(18), 'FN_3': np.int64(26), 'TP_4': np.int64(29), 'TN_4': np.int64(55), 'FP_4': np.int64(29), 'FN_4': np.int64(19), 'TP_5': np.int64(4), 'TN_5': np.int64(107), 'FP_5': np.int64(10), 'FN_5': np.int64(11)}
-[2025-06-03 01:16:20,939][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-320
-[2025-06-03 01:16:20,940][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-320/config.json
-[2025-06-03 01:16:21,707][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-320/model.safetensors
-[2025-06-03 01:16:22,380][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-224] due to args.save_total_limit
-[2025-06-03 01:16:22,454][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-288] due to args.save_total_limit
-[2025-06-03 01:16:24,369][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:24,370][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:24,371][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:24,371][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:24,588][transformers][INFO] - {'accuracy': 0.553030303030303, 'RMSE': 28.4977404739606, 'QWK': 0.4124368854637257, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.23824175824175825, 'Micro_F1': 0.553030303030303, 'Weighted_F1': 0.503096903096903, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(30), 'TN_3': np.int64(58), 'FP_3': np.int64(10), 'FN_3': np.int64(34), 'TP_4': np.int64(43), 'TN_4': np.int64(35), 'FP_4': np.int64(49), 'FN_4': np.int64(5), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 01:16:24,590][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-352
-[2025-06-03 01:16:24,591][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-352/config.json
-[2025-06-03 01:16:25,424][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-352/model.safetensors
-[2025-06-03 01:16:27,956][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:27,958][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:27,958][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:27,958][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:28,176][transformers][INFO] - {'accuracy': 0.5606060606060606, 'RMSE': 28.91995221924885, 'QWK': 0.3948976880148818, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2420879120879121, 'Micro_F1': 0.5606060606060606, 'Weighted_F1': 0.5124209124209125, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(31), 'TN_3': np.int64(59), 'FP_3': np.int64(9), 'FN_3': np.int64(33), 'TP_4': np.int64(43), 'TN_4': np.int64(35), 'FP_4': np.int64(49), 'FN_4': np.int64(5), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 01:16:28,179][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-384
-[2025-06-03 01:16:28,180][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-384/config.json
-[2025-06-03 01:16:29,024][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-384/model.safetensors
-[2025-06-03 01:16:29,737][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-352] due to args.save_total_limit
-[2025-06-03 01:16:31,635][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:31,637][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:31,637][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:31,637][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:31,855][transformers][INFO] - {'accuracy': 0.5681818181818182, 'RMSE': 28.06917861068948, 'QWK': 0.43073248407643305, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.24539239814055236, 'Micro_F1': 0.5681818181818182, 'Weighted_F1': 0.519352673577448, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(32), 'TN_3': np.int64(58), 'FP_3': np.int64(10), 'FN_3': np.int64(32), 'TP_4': np.int64(43), 'TN_4': np.int64(37), 'FP_4': np.int64(47), 'FN_4': np.int64(5), 'TP_5': np.int64(0), 'TN_5': np.int64(117), 'FP_5': np.int64(0), 'FN_5': np.int64(15)}
-[2025-06-03 01:16:31,857][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-416
-[2025-06-03 01:16:31,858][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-416/config.json
-[2025-06-03 01:16:32,680][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-416/model.safetensors
-[2025-06-03 01:16:33,374][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-384] due to args.save_total_limit
-[2025-06-03 01:16:35,259][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:35,260][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:35,261][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:35,261][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:35,477][transformers][INFO] - {'accuracy': 0.5606060606060606, 'RMSE': 30.15113445777636, 'QWK': 0.4218640504555011, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2788798309178744, 'Micro_F1': 0.5606060606060606, 'Weighted_F1': 0.5376500512370077, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(33), 'TN_3': np.int64(57), 'FP_3': np.int64(11), 'FN_3': np.int64(31), 'TP_4': np.int64(39), 'TN_4': np.int64(43), 'FP_4': np.int64(41), 'FN_4': np.int64(9), 'TP_5': np.int64(2), 'TN_5': np.int64(111), 'FP_5': np.int64(6), 'FN_5': np.int64(13)}
-[2025-06-03 01:16:35,479][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-448
-[2025-06-03 01:16:35,480][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-448/config.json
-[2025-06-03 01:16:36,385][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-448/model.safetensors
-[2025-06-03 01:16:37,071][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-416] due to args.save_total_limit
-[2025-06-03 01:16:38,970][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:38,972][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:38,972][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:38,972][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:39,203][transformers][INFO] - {'accuracy': 0.5681818181818182, 'RMSE': 30.550504633038933, 'QWK': 0.4841656516443361, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.31708817498291186, 'Micro_F1': 0.5681818181818182, 'Weighted_F1': 0.5635369415273722, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(36), 'TN_3': np.int64(56), 'FP_3': np.int64(12), 'FN_3': np.int64(28), 'TP_4': np.int64(33), 'TN_4': np.int64(51), 'FP_4': np.int64(33), 'FN_4': np.int64(15), 'TP_5': np.int64(6), 'TN_5': np.int64(105), 'FP_5': np.int64(12), 'FN_5': np.int64(9)}
-[2025-06-03 01:16:39,206][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-480
-[2025-06-03 01:16:39,208][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-480/config.json
-[2025-06-03 01:16:40,054][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-480/model.safetensors
-[2025-06-03 01:16:40,811][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-320] due to args.save_total_limit
-[2025-06-03 01:16:40,870][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-448] due to args.save_total_limit
-[2025-06-03 01:16:42,766][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:42,768][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:42,768][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:42,768][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:42,986][transformers][INFO] - {'accuracy': 0.6060606060606061, 'RMSE': 27.633971188310298, 'QWK': 0.46896551724137936, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2849877450980392, 'Micro_F1': 0.6060606060606061, 'Weighted_F1': 0.5695558526440879, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(38), 'TN_3': np.int64(56), 'FP_3': np.int64(12), 'FN_3': np.int64(26), 'TP_4': np.int64(41), 'TN_4': np.int64(45), 'FP_4': np.int64(39), 'FN_4': np.int64(7), 'TP_5': np.int64(1), 'TN_5': np.int64(116), 'FP_5': np.int64(1), 'FN_5': np.int64(14)}
-[2025-06-03 01:16:42,988][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-512
-[2025-06-03 01:16:42,989][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-512/config.json
-[2025-06-03 01:16:43,899][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-512/model.safetensors
-[2025-06-03 01:16:46,436][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:46,438][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:46,438][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:46,438][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:46,655][transformers][INFO] - {'accuracy': 0.5909090909090909, 'RMSE': 28.06917861068948, 'QWK': 0.45140664961636834, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2782546864899806, 'Micro_F1': 0.5909090909090909, 'Weighted_F1': 0.5544279250161603, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(36), 'TN_3': np.int64(56), 'FP_3': np.int64(12), 'FN_3': np.int64(28), 'TP_4': np.int64(41), 'TN_4': np.int64(43), 'FP_4': np.int64(41), 'FN_4': np.int64(7), 'TP_5': np.int64(1), 'TN_5': np.int64(116), 'FP_5': np.int64(1), 'FN_5': np.int64(14)}
-[2025-06-03 01:16:46,658][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-544
-[2025-06-03 01:16:46,659][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-544/config.json
-[2025-06-03 01:16:47,506][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-544/model.safetensors
-[2025-06-03 01:16:48,171][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-512] due to args.save_total_limit
-[2025-06-03 01:16:50,121][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:50,123][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:50,123][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:50,123][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:50,350][transformers][INFO] - {'accuracy': 0.5909090909090909, 'RMSE': 28.06917861068948, 'QWK': 0.4686648501362397, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.2956766917293233, 'Micro_F1': 0.5909090909090909, 'Weighted_F1': 0.5628844839371155, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(36), 'TN_3': np.int64(56), 'FP_3': np.int64(12), 'FN_3': np.int64(28), 'TP_4': np.int64(40), 'TN_4': np.int64(44), 'FP_4': np.int64(40), 'FN_4': np.int64(8), 'TP_5': np.int64(2), 'TN_5': np.int64(115), 'FP_5': np.int64(2), 'FN_5': np.int64(13)}
-[2025-06-03 01:16:50,354][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-576
-[2025-06-03 01:16:50,355][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-576/config.json
-[2025-06-03 01:16:51,317][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-576/model.safetensors
-[2025-06-03 01:16:52,301][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-544] due to args.save_total_limit
-[2025-06-03 01:16:54,524][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:54,526][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:54,526][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:54,526][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:54,768][transformers][INFO] - {'accuracy': 0.553030303030303, 'RMSE': 29.74640288923158, 'QWK': 0.45287304110833526, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.28750471698113206, 'Micro_F1': 0.553030303030303, 'Weighted_F1': 0.5359205260148655, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(32), 'TN_3': np.int64(58), 'FP_3': np.int64(10), 'FN_3': np.int64(32), 'TP_4': np.int64(38), 'TN_4': np.int64(42), 'FP_4': np.int64(42), 'FN_4': np.int64(10), 'TP_5': np.int64(3), 'TN_5': np.int64(110), 'FP_5': np.int64(7), 'FN_5': np.int64(12)}
-[2025-06-03 01:16:54,772][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-608
-[2025-06-03 01:16:54,773][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-608/config.json
-[2025-06-03 01:16:55,881][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-608/model.safetensors
-[2025-06-03 01:16:56,738][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-576] due to args.save_total_limit
-[2025-06-03 01:16:58,663][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:16:58,664][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:16:58,664][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:16:58,664][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:16:58,881][transformers][INFO] - {'accuracy': 0.5606060606060606, 'RMSE': 28.91995221924885, 'QWK': 0.45251262322673724, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.28048160173160175, 'Micro_F1': 0.5606060606060606, 'Weighted_F1': 0.5372786304604487, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(34), 'TN_3': np.int64(56), 'FP_3': np.int64(12), 'FN_3': np.int64(30), 'TP_4': np.int64(38), 'TN_4': np.int64(42), 'FP_4': np.int64(42), 'FN_4': np.int64(10), 'TP_5': np.int64(2), 'TN_5': np.int64(113), 'FP_5': np.int64(4), 'FN_5': np.int64(13)}
-[2025-06-03 01:16:58,883][transformers.trainer][INFO] - Saving model checkpoint to /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-640
-[2025-06-03 01:16:58,884][transformers.configuration_utils][INFO] - Configuration saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-640/config.json
-[2025-06-03 01:16:59,809][transformers.modeling_utils][INFO] - Model weights saved in /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-640/model.safetensors
-[2025-06-03 01:17:00,541][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-608] due to args.save_total_limit
-[2025-06-03 01:17:00,618][transformers.trainer][INFO] - 
-
-Training completed. Do not forget to share your model on huggingface.co/models =)
-
-
-[2025-06-03 01:17:00,618][transformers.trainer][INFO] - Loading best model from /workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-480 (score: 0.4841656516443361).
-[2025-06-03 01:17:00,733][transformers.trainer][INFO] - Deleting older checkpoint [/workspace/jbcs2025/outputs/2025-06-03/01-15-35/results/checkpoint-640] due to args.save_total_limit
-[2025-06-03 01:17:00,825][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:17:00,827][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:17:00,827][transformers.trainer][INFO] -   Num examples = 132
-[2025-06-03 01:17:00,827][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:17:01,061][transformers][INFO] - {'accuracy': 0.5681818181818182, 'RMSE': 30.550504633038933, 'QWK': 0.4841656516443361, 'HDIV': 0.007575757575757569, 'Macro_F1': 0.31708817498291186, 'Micro_F1': 0.5681818181818182, 'Weighted_F1': 0.5635369415273722, 'TP_0': np.int64(0), 'TN_0': np.int64(131), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(132), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(0), 'TN_2': np.int64(128), 'FP_2': np.int64(0), 'FN_2': np.int64(4), 'TP_3': np.int64(36), 'TN_3': np.int64(56), 'FP_3': np.int64(12), 'FN_3': np.int64(28), 'TP_4': np.int64(33), 'TN_4': np.int64(51), 'FP_4': np.int64(33), 'FN_4': np.int64(15), 'TP_5': np.int64(6), 'TN_5': np.int64(105), 'FP_5': np.int64(12), 'FN_5': np.int64(9)}
-[2025-06-03 01:17:01,066][__main__][INFO] - Training completed successfully.
-[2025-06-03 01:17:01,066][__main__][INFO] - Running on Test
-[2025-06-03 01:17:01,066][transformers.trainer][INFO] - The following columns in the Evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year. If id_prompt, reference, grades, id, essay_text, prompt, supporting_text, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-03 01:17:01,068][transformers.trainer][INFO] - 
-***** Running Evaluation *****
-[2025-06-03 01:17:01,068][transformers.trainer][INFO] -   Num examples = 138
-[2025-06-03 01:17:01,068][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-03 01:17:01,288][transformers][INFO] - {'accuracy': 0.644927536231884, 'RMSE': 26.37521893583148, 'QWK': 0.5818181818181818, 'HDIV': 0.007246376811594235, 'Macro_F1': 0.35879198887141794, 'Micro_F1': 0.644927536231884, 'Weighted_F1': 0.643663118795876, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(137), 'FP_1': np.int64(0), 'FN_1': np.int64(1), 'TP_2': np.int64(3), 'TN_2': np.int64(124), 'FP_2': np.int64(5), 'FN_2': np.int64(6), 'TP_3': np.int64(53), 'TN_3': np.int64(45), 'FP_3': np.int64(17), 'FN_3': np.int64(23), 'TP_4': np.int64(30), 'TN_4': np.int64(70), 'FP_4': np.int64(22), 'FN_4': np.int64(16), 'TP_5': np.int64(3), 'TN_5': np.int64(128), 'FP_5': np.int64(5), 'FN_5': np.int64(2)}
-[2025-06-03 01:17:01,290][transformers.trainer][INFO] - Saving model checkpoint to ./results/best_model
-[2025-06-03 01:17:01,292][transformers.configuration_utils][INFO] - Configuration saved in ./results/best_model/config.json
-[2025-06-03 01:17:02,118][transformers.modeling_utils][INFO] - Model weights saved in ./results/best_model/model.safetensors
-[2025-06-03 01:17:02,120][transformers.tokenization_utils_base][INFO] - tokenizer config file saved in ./results/best_model/tokenizer_config.json
-[2025-06-03 01:17:02,120][transformers.tokenization_utils_base][INFO] - Special tokens file saved in ./results/best_model/special_tokens_map.json
-[2025-06-03 01:17:02,129][__main__][INFO] - Model and tokenizer saved to ./results/best_model
-[2025-06-03 01:17:02,131][__main__][INFO] - Fine Tuning Finished.
-[2025-06-03 01:17:02,641][__main__][INFO] - Total emissions: 0.0005 kg CO2eq
+version https://git-lfs.github.com/spec/v1
+oid sha256:909f41433c9d689525f2322ecb93ba75af6ffc5d2d4b749973163a5c7bfa8047
+size 60017

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C5/emissions.csv

@@ -1,2 +1,3 @@
-timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
-2025-06-03T01:19:56,jbcs2025,6754b4fb-f88f-44db-a917-92957d3f2e1d,bert-base-portuguese-cased-encoder_ordinal_coral-C5,55.995558484923095,0.0003189154257841971,5.695370033144069e-06,99.45384615384616,223.96667440869567,70.0,0.0013054452728597332,0.003316350986381167,0.0010691587146914876,0.005690954973932388,France,FRA,île-de-france,,,Linux-5.15.0-136-generic-x86_64-with-glibc2.35,3.12.10,3.0.2,192,INTEL(R) XEON(R) PLATINUM 8568Y+,1,1 x NVIDIA H200,2.3494,48.8558,2015.3635139465332,machine,N,1.0
+version https://git-lfs.github.com/spec/v1
+oid sha256:99ab03a0c474638beca900164c51a22e4526ab6fc8daf5bec4d98bf10f4a52a7
+size 861

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C5/evaluation_results.csv

@@ -1,4 +1,3 @@
-eval_loss,eval_model_preparation_time,eval_accuracy,eval_RMSE,eval_QWK,eval_HDIV,eval_Macro_F1,eval_Micro_F1,eval_Weighted_F1,eval_TP_0,eval_TN_0,eval_FP_0,eval_FN_0,eval_TP_1,eval_TN_1,eval_FP_1,eval_FN_1,eval_TP_2,eval_TN_2,eval_FP_2,eval_FN_2,eval_TP_3,eval_TN_3,eval_FP_3,eval_FN_3,eval_TP_4,eval_TN_4,eval_FP_4,eval_FN_4,eval_TP_5,eval_TN_5,eval_FP_5,eval_FN_5,eval_runtime,eval_samples_per_second,eval_steps_per_second,epoch,reference,timestamp,id
-5.116938591003418,0.0016,0.20454545454545456,67.14976477316141,-0.1617848861969433,0.13636363636363635,0.12330549503752118,0.20454545454545456,0.17261531436368038,0,115,0,17,7,71,25,29,7,58,54,13,13,73,26,20,0,108,0,24,0,130,0,2,0.5366,245.972,16.771,-1,validation_before_training,2025-06-03 01:19:07,bert-base-portuguese-cased-encoder_ordinal_coral-C5
-2.769163131713867,0.0016,0.36363636363636365,47.60952285695233,0.5714285714285714,0.06818181818181823,0.2562339695811547,0.36363636363636365,0.32231195920655803,0,115,0,17,7,77,19,29,8,94,18,12,19,72,27,14,14,88,20,10,0,130,0,2,0.2299,574.246,39.153,12.0,validation_after_training,2025-06-03 01:19:07,bert-base-portuguese-cased-encoder_ordinal_coral-C5
-2.8962960243225098,0.0016,0.30434782608695654,49.57792870313113,0.5580397607106169,0.050724637681159424,0.22814148207817472,0.30434782608695654,0.2802363594448202,1,115,1,21,6,86,20,26,12,82,32,12,6,87,26,19,17,89,17,15,0,135,0,3,0.2296,600.969,39.194,12.0,test_results,2025-06-03 01:19:07,bert-base-portuguese-cased-encoder_ordinal_coral-C5
+version https://git-lfs.github.com/spec/v1
+oid sha256:7c6e112922e6ed27be9539c069d96db5f56fb29bb758131760bce76b27283ebd
+size 1506

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C5/results/best_model/config.json

@@ -1,45 +1,3 @@
-{
-  "architectures": [
-    "BertForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cf1f6d6785c3b5bcfc91fad895c1ed8a279abdc99a665ea0767faf219a6e2d9
+size 1047

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C5/results/best_model/special_tokens_map.json

@@ -1,7 +1,3 @@
-{
-  "cls_token": "[CLS]",
-  "mask_token": "[MASK]",
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "unk_token": "[UNK]"
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6d346be366a7d1d48332dbc9fdf3bf8960b5d879522b7799ddba59e76237ee3
+size 125

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C5/results/best_model/tokenizer_config.json

@@ -1,58 +1,3 @@
-{
-  "added_tokens_decoder": {
-    "0": {
-      "content": "[PAD]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "100": {
-      "content": "[UNK]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "101": {
-      "content": "[CLS]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "102": {
-      "content": "[SEP]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "103": {
-      "content": "[MASK]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    }
-  },
-  "clean_up_tokenization_spaces": true,
-  "cls_token": "[CLS]",
-  "do_basic_tokenize": true,
-  "do_lower_case": false,
-  "extra_special_tokens": {},
-  "mask_token": "[MASK]",
-  "model_max_length": 1000000000000000019884624838656,
-  "never_split": null,
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "strip_accents": null,
-  "tokenize_chinese_chars": true,
-  "tokenizer_class": "BertTokenizer",
-  "unk_token": "[UNK]"
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ab044e4a71cdb2a5cff548e16d3bcd46a757848ef861743426c44a134b00da1
+size 1301

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C5/results/checkpoint-224/config.json

@@ -1,45 +1,3 @@
-{
-  "architectures": [
-    "BertForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "directionality": "bidi",
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "output_past": true,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.52.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 29794
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cf1f6d6785c3b5bcfc91fad895c1ed8a279abdc99a665ea0767faf219a6e2d9
+size 1047

runs/encoder_models/base_models/bertimbau/bert-base-portuguese-cased-encoder_ordinal_coral-C5/results/checkpoint-224/trainer_state.json

@@ -1,337 +1,3 @@
-{
-  "best_global_step": 224,
-  "best_metric": 0.5714285714285714,
-  "best_model_checkpoint": "/workspace/jbcs2025/outputs/2025-06-03/01-18-57/results/checkpoint-224",
-  "epoch": 7.0,
-  "eval_steps": 500,
-  "global_step": 224,
-  "is_hyper_param_search": false,
-  "is_local_process_zero": true,
-  "is_world_process_zero": true,
-  "log_history": [
-    {
-      "epoch": 1.0,
-      "eval_FN_0": 17,
-      "eval_FN_1": 36,
-      "eval_FN_2": 0,
-      "eval_FN_3": 33,
-      "eval_FN_4": 24,
-      "eval_FN_5": 2,
-      "eval_FP_0": 0,
-      "eval_FP_1": 0,
-      "eval_FP_2": 112,
-      "eval_FP_3": 0,
-      "eval_FP_4": 0,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.015151515151515138,
-      "eval_Macro_F1": 0.043859649122807015,
-      "eval_Micro_F1": 0.15151515151515152,
-      "eval_QWK": 0.0,
-      "eval_RMSE": 55.158174756097964,
-      "eval_TN_0": 115,
-      "eval_TN_1": 96,
-      "eval_TN_2": 0,
-      "eval_TN_3": 99,
-      "eval_TN_4": 108,
-      "eval_TN_5": 130,
-      "eval_TP_0": 0,
-      "eval_TP_1": 0,
-      "eval_TP_2": 20,
-      "eval_TP_3": 0,
-      "eval_TP_4": 0,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.03987240829346092,
-      "eval_accuracy": 0.15151515151515152,
-      "eval_loss": 3.3801538944244385,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2248,
-      "eval_samples_per_second": 587.302,
-      "eval_steps_per_second": 40.043,
-      "step": 32
-    },
-    {
-      "epoch": 2.0,
-      "eval_FN_0": 17,
-      "eval_FN_1": 33,
-      "eval_FN_2": 14,
-      "eval_FN_3": 2,
-      "eval_FN_4": 24,
-      "eval_FN_5": 2,
-      "eval_FP_0": 0,
-      "eval_FP_1": 11,
-      "eval_FP_2": 18,
-      "eval_FP_3": 63,
-      "eval_FP_4": 0,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.007575757575757569,
-      "eval_Macro_F1": 0.1468193748508709,
-      "eval_Micro_F1": 0.30303030303030304,
-      "eval_QWK": 0.42965881615474166,
-      "eval_RMSE": 48.36728170358491,
-      "eval_TN_0": 115,
-      "eval_TN_1": 85,
-      "eval_TN_2": 94,
-      "eval_TN_3": 36,
-      "eval_TN_4": 108,
-      "eval_TN_5": 130,
-      "eval_TP_0": 0,
-      "eval_TP_1": 3,
-      "eval_TP_2": 6,
-      "eval_TP_3": 31,
-      "eval_TP_4": 0,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.1960968308713477,
-      "eval_accuracy": 0.30303030303030304,
-      "eval_loss": 3.023169755935669,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2338,
-      "eval_samples_per_second": 564.671,
-      "eval_steps_per_second": 38.5,
-      "step": 64
-    },
-    {
-      "epoch": 3.0,
-      "eval_FN_0": 15,
-      "eval_FN_1": 27,
-      "eval_FN_2": 10,
-      "eval_FN_3": 7,
-      "eval_FN_4": 24,
-      "eval_FN_5": 2,
-      "eval_FP_0": 0,
-      "eval_FP_1": 19,
-      "eval_FP_2": 24,
-      "eval_FP_3": 38,
-      "eval_FP_4": 4,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.037878787878787845,
-      "eval_Macro_F1": 0.23303819339777468,
-      "eval_Micro_F1": 0.3560606060606061,
-      "eval_QWK": 0.4981734771897036,
-      "eval_RMSE": 46.5800061152526,
-      "eval_TN_0": 115,
-      "eval_TN_1": 77,
-      "eval_TN_2": 88,
-      "eval_TN_3": 61,
-      "eval_TN_4": 104,
-      "eval_TN_5": 130,
-      "eval_TP_0": 2,
-      "eval_TP_1": 9,
-      "eval_TP_2": 10,
-      "eval_TP_3": 26,
-      "eval_TP_4": 0,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.29395512443418936,
-      "eval_accuracy": 0.3560606060606061,
-      "eval_loss": 2.536144733428955,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.231,
-      "eval_samples_per_second": 571.494,
-      "eval_steps_per_second": 38.966,
-      "step": 96
-    },
-    {
-      "epoch": 3.125,
-      "grad_norm": 11.251823425292969,
-      "learning_rate": 4.696180555555556e-05,
-      "loss": 3.3704,
-      "step": 100
-    },
-    {
-      "epoch": 4.0,
-      "eval_FN_0": 10,
-      "eval_FN_1": 32,
-      "eval_FN_2": 17,
-      "eval_FN_3": 7,
-      "eval_FN_4": 18,
-      "eval_FN_5": 2,
-      "eval_FP_0": 3,
-      "eval_FP_1": 12,
-      "eval_FP_2": 11,
-      "eval_FP_3": 48,
-      "eval_FP_4": 12,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.05303030303030298,
-      "eval_Macro_F1": 0.2700884757875779,
-      "eval_Micro_F1": 0.3484848484848485,
-      "eval_QWK": 0.5552374301675977,
-      "eval_RMSE": 48.36728170358491,
-      "eval_TN_0": 112,
-      "eval_TN_1": 84,
-      "eval_TN_2": 101,
-      "eval_TN_3": 51,
-      "eval_TN_4": 96,
-      "eval_TN_5": 130,
-      "eval_TP_0": 7,
-      "eval_TP_1": 4,
-      "eval_TP_2": 3,
-      "eval_TP_3": 26,
-      "eval_TP_4": 6,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.3089182890355696,
-      "eval_accuracy": 0.3484848484848485,
-      "eval_loss": 2.656505823135376,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2253,
-      "eval_samples_per_second": 585.777,
-      "eval_steps_per_second": 39.939,
-      "step": 128
-    },
-    {
-      "epoch": 5.0,
-      "eval_FN_0": 17,
-      "eval_FN_1": 29,
-      "eval_FN_2": 15,
-      "eval_FN_3": 11,
-      "eval_FN_4": 17,
-      "eval_FN_5": 2,
-      "eval_FP_0": 0,
-      "eval_FP_1": 17,
-      "eval_FP_2": 15,
-      "eval_FP_3": 44,
-      "eval_FP_4": 15,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.05303030303030298,
-      "eval_Macro_F1": 0.20535426731078907,
-      "eval_Micro_F1": 0.3106060606060606,
-      "eval_QWK": 0.48137941307910026,
-      "eval_RMSE": 50.572480239511265,
-      "eval_TN_0": 115,
-      "eval_TN_1": 79,
-      "eval_TN_2": 97,
-      "eval_TN_3": 55,
-      "eval_TN_4": 93,
-      "eval_TN_5": 130,
-      "eval_TP_0": 0,
-      "eval_TP_1": 7,
-      "eval_TP_2": 5,
-      "eval_TP_3": 22,
-      "eval_TP_4": 7,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.26796223100570926,
-      "eval_accuracy": 0.3106060606060606,
-      "eval_loss": 2.6958184242248535,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2225,
-      "eval_samples_per_second": 593.141,
-      "eval_steps_per_second": 40.441,
-      "step": 160
-    },
-    {
-      "epoch": 6.0,
-      "eval_FN_0": 14,
-      "eval_FN_1": 32,
-      "eval_FN_2": 10,
-      "eval_FN_3": 12,
-      "eval_FN_4": 19,
-      "eval_FN_5": 2,
-      "eval_FP_0": 3,
-      "eval_FP_1": 14,
-      "eval_FP_2": 28,
-      "eval_FP_3": 33,
-      "eval_FP_4": 11,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.045454545454545414,
-      "eval_Macro_F1": 0.24776732004368188,
-      "eval_Micro_F1": 0.32575757575757575,
-      "eval_QWK": 0.5637655688851532,
-      "eval_RMSE": 45.79268169663901,
-      "eval_TN_0": 112,
-      "eval_TN_1": 82,
-      "eval_TN_2": 84,
-      "eval_TN_3": 66,
-      "eval_TN_4": 97,
-      "eval_TN_5": 130,
-      "eval_TP_0": 3,
-      "eval_TP_1": 4,
-      "eval_TP_2": 10,
-      "eval_TP_3": 21,
-      "eval_TP_4": 5,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.2923916829464056,
-      "eval_accuracy": 0.32575757575757575,
-      "eval_loss": 2.542938232421875,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.221,
-      "eval_samples_per_second": 597.22,
-      "eval_steps_per_second": 40.72,
-      "step": 192
-    },
-    {
-      "epoch": 6.25,
-      "grad_norm": 8.958661079406738,
-      "learning_rate": 3.828125e-05,
-      "loss": 1.9395,
-      "step": 200
-    },
-    {
-      "epoch": 7.0,
-      "eval_FN_0": 17,
-      "eval_FN_1": 29,
-      "eval_FN_2": 12,
-      "eval_FN_3": 14,
-      "eval_FN_4": 10,
-      "eval_FN_5": 2,
-      "eval_FP_0": 0,
-      "eval_FP_1": 19,
-      "eval_FP_2": 18,
-      "eval_FP_3": 27,
-      "eval_FP_4": 20,
-      "eval_FP_5": 0,
-      "eval_HDIV": 0.06818181818181823,
-      "eval_Macro_F1": 0.2562339695811547,
-      "eval_Micro_F1": 0.36363636363636365,
-      "eval_QWK": 0.5714285714285714,
-      "eval_RMSE": 47.60952285695233,
-      "eval_TN_0": 115,
-      "eval_TN_1": 77,
-      "eval_TN_2": 94,
-      "eval_TN_3": 72,
-      "eval_TN_4": 88,
-      "eval_TN_5": 130,
-      "eval_TP_0": 0,
-      "eval_TP_1": 7,
-      "eval_TP_2": 8,
-      "eval_TP_3": 19,
-      "eval_TP_4": 14,
-      "eval_TP_5": 0,
-      "eval_Weighted_F1": 0.32231195920655803,
-      "eval_accuracy": 0.36363636363636365,
-      "eval_loss": 2.769163131713867,
-      "eval_model_preparation_time": 0.0016,
-      "eval_runtime": 0.2203,
-      "eval_samples_per_second": 599.289,
-      "eval_steps_per_second": 40.861,
-      "step": 224
-    }
-  ],
-  "logging_steps": 100,
-  "max_steps": 640,
-  "num_input_tokens_seen": 0,
-  "num_train_epochs": 20,
-  "save_steps": 500,
-  "stateful_callbacks": {
-    "EarlyStoppingCallback": {
-      "args": {
-        "early_stopping_patience": 5,
-        "early_stopping_threshold": 0.0
-      },
-      "attributes": {
-        "early_stopping_patience_counter": 0
-      }
-    },
-    "TrainerControl": {
-      "args": {
-        "should_epoch_stop": false,
-        "should_evaluate": false,
-        "should_log": false,
-        "should_save": true,
-        "should_training_stop": false
-      },
-      "attributes": {}
-    }
-  },
-  "total_flos": 920913498624000.0,
-  "train_batch_size": 16,
-  "trial_name": null,
-  "trial_params": null
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:66b08305f9f86bd3e495015fe0871437f94cccf6eb09de70f2ec4d9869fb6601
+size 8952