End of training

README.md

@@ -1,10 +1,11 @@
 ---
-license: apache-2.0
-base_model: Fan-s/reddit-tc-bert
+license: mit
+base_model: Tsubasaz/clinical-pubmed-bert-base-512
 tags:
 - generated_from_trainer
 metrics:
-- f1
+- precision
+- recall
 model-index:
 - name: model
   results: []
@@ -15,10 +16,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # model
 
-This model is a fine-tuned version of [Fan-s/reddit-tc-bert](https://huggingface.co/Fan-s/reddit-tc-bert) on the None dataset.
+This model is a fine-tuned version of [Tsubasaz/clinical-pubmed-bert-base-512](https://huggingface.co/Tsubasaz/clinical-pubmed-bert-base-512) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3981
-- F1: 0.4000
+- Loss: 0.3511
+- Precision: 0.6103
+- Recall: 0.5640
 
 ## Model description
 
@@ -37,31 +39,33 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-06
-- train_batch_size: 36
-- eval_batch_size: 36
+- learning_rate: 3e-06
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 8
+- num_epochs: 10
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:------:|
-| No log        | 1.0   | 91   | 0.4630          | 0.1531 |
-| No log        | 2.0   | 182  | 0.4290          | 0.1887 |
-| No log        | 3.0   | 273  | 0.4143          | 0.2364 |
-| No log        | 4.0   | 364  | 0.4074          | 0.3502 |
-| No log        | 5.0   | 455  | 0.4037          | 0.2719 |
-| 0.3843        | 6.0   | 546  | 0.3991          | 0.3893 |
-| 0.3843        | 7.0   | 637  | 0.3985          | 0.3828 |
-| 0.3843        | 8.0   | 728  | 0.3981          | 0.4000 |
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
+| No log        | 1.0   | 128  | 0.4393          | 0.0       | 0.0    |
+| No log        | 2.0   | 256  | 0.3958          | 0.5714    | 0.1706 |
+| No log        | 3.0   | 384  | 0.3785          | 0.5690    | 0.3128 |
+| 0.4046        | 4.0   | 512  | 0.3676          | 0.5789    | 0.5213 |
+| 0.4046        | 5.0   | 640  | 0.3606          | 0.6532    | 0.3839 |
+| 0.4046        | 6.0   | 768  | 0.3597          | 0.6549    | 0.4408 |
+| 0.4046        | 7.0   | 896  | 0.3584          | 0.6376    | 0.4502 |
+| 0.3046        | 8.0   | 1024 | 0.3518          | 0.6310    | 0.5024 |
+| 0.3046        | 9.0   | 1152 | 0.3511          | 0.6133    | 0.5261 |
+| 0.3046        | 10.0  | 1280 | 0.3511          | 0.6103    | 0.5640 |
 
 
 ### Framework versions
 
-- Transformers 4.35.0
+- Transformers 4.35.2
 - Pytorch 2.0.0
-- Datasets 2.14.6
-- Tokenizers 0.14.1
+- Datasets 2.15.0
+- Tokenizers 0.15.0

config.json

@@ -1,11 +1,10 @@
 {
-  "_name_or_path": "Fan-s/reddit-tc-bert",
+  "_name_or_path": "Tsubasaz/clinical-pubmed-bert-base-512",
   "architectures": [
     "BertForSequenceClassification"
   ],
   "attention_probs_dropout_prob": 0.1,
   "classifier_dropout": null,
-  "gradient_checkpointing": false,
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
   "hidden_size": 768,
@@ -28,7 +27,7 @@
   "position_embedding_type": "absolute",
   "problem_type": "single_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.35.0",
+  "transformers_version": "4.35.2",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 30522

model.safetensors

@@ -1,3 +1,3 @@
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-oid sha256:c01ff4818ed18d0fc1d3bd80845e90cb1cf600515a723a69a4a72d18ae659123
+oid sha256:ed415934ece8ee8a90b151152495720a03450bf2c3caf5d7f4faf9f0e7a0927f
 size 437958648

tokenizer_config.json

@@ -8,7 +8,7 @@
       "single_word": false,
       "special": true
     },
-    "100": {
+    "1": {
       "content": "[UNK]",
       "lstrip": false,
       "normalized": false,
@@ -16,7 +16,7 @@
       "single_word": false,
       "special": true
     },
-    "101": {
+    "2": {
       "content": "[CLS]",
       "lstrip": false,
       "normalized": false,
@@ -24,7 +24,7 @@
       "single_word": false,
       "special": true
     },
-    "102": {
+    "3": {
       "content": "[SEP]",
       "lstrip": false,
       "normalized": false,
@@ -32,7 +32,7 @@
       "single_word": false,
       "special": true
     },
-    "103": {
+    "4": {
       "content": "[MASK]",
       "lstrip": false,
       "normalized": false,
@@ -43,20 +43,15 @@
   },
   "clean_up_tokenization_spaces": true,
   "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
   "do_lower_case": true,
   "mask_token": "[MASK]",
-  "max_length": 128,
-  "model_max_length": 512,
-  "pad_to_multiple_of": null,
+  "model_max_length": 1000000000000000019884624838656,
+  "never_split": null,
   "pad_token": "[PAD]",
-  "pad_token_type_id": 0,
-  "padding_side": "right",
   "sep_token": "[SEP]",
-  "stride": 0,
   "strip_accents": null,
   "tokenize_chinese_chars": true,
   "tokenizer_class": "BertTokenizer",
-  "truncation_side": "right",
-  "truncation_strategy": "longest_first",
   "unk_token": "[UNK]"
 }

training_args.bin

@@ -1,3 +1,3 @@
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+oid sha256:3f4faeefaa88f45ece3a78c6e7619be4f3b8c192526b2a92369a65a46abb2586
 size 4091