End of training

README.md

@@ -1,12 +1,27 @@
 ---
+language:
+- en
 base_model: Hartunka/tiny_bert_km_50_v1
 tags:
 - generated_from_trainer
+datasets:
+- glue
 metrics:
 - accuracy
 model-index:
 - name: tiny_bert_km_50_v1_rte
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: GLUE RTE
+      type: glue
+      args: rte
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.5054151624548736
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -14,9 +29,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 # tiny_bert_km_50_v1_rte
 
-This model is a fine-tuned version of [Hartunka/tiny_bert_km_50_v1](https://huggingface.co/Hartunka/tiny_bert_km_50_v1) on an unknown dataset.
+This model is a fine-tuned version of [Hartunka/tiny_bert_km_50_v1](https://huggingface.co/Hartunka/tiny_bert_km_50_v1) on the GLUE RTE dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7591
+- Loss: 0.6951
 - Accuracy: 0.5054
 
 ## Model description

all_results.json

@@ -0,0 +1,15 @@
+{
+    "epoch": 6.0,
+    "eval_accuracy": 0.5054151624548736,
+    "eval_loss": 0.6951221227645874,
+    "eval_runtime": 0.1361,
+    "eval_samples": 277,
+    "eval_samples_per_second": 2034.537,
+    "eval_steps_per_second": 14.69,
+    "total_flos": 391780256993280.0,
+    "train_loss": 0.6523992617925009,
+    "train_runtime": 15.3656,
+    "train_samples": 2490,
+    "train_samples_per_second": 8102.502,
+    "train_steps_per_second": 32.54
+}

eval_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 6.0,
+    "eval_accuracy": 0.5054151624548736,
+    "eval_loss": 0.6951221227645874,
+    "eval_runtime": 0.1361,
+    "eval_samples": 277,
+    "eval_samples_per_second": 2034.537,
+    "eval_steps_per_second": 14.69
+}

logs/events.out.tfevents.1744815022.s_004_m

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9b2f428eaf9753a99055875c1733a96fff7b7dfca5654881cdd2acc0cc25d90e
+size 249

train_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 6.0,
+    "total_flos": 391780256993280.0,
+    "train_loss": 0.6523992617925009,
+    "train_runtime": 15.3656,
+    "train_samples": 2490,
+    "train_samples_per_second": 8102.502,
+    "train_steps_per_second": 32.54
+}

trainer_state.json

@@ -0,0 +1,126 @@
+{
+  "best_metric": 0.6951221227645874,
+  "best_model_checkpoint": "tiny_bert_km_50_v1_rte/checkpoint-10",
+  "epoch": 6.0,
+  "eval_steps": 500,
+  "global_step": 60,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 1.0,
+      "grad_norm": 0.6421326398849487,
+      "learning_rate": 4.9e-05,
+      "loss": 0.6977,
+      "step": 10
+    },
+    {
+      "epoch": 1.0,
+      "eval_accuracy": 0.5054151624548736,
+      "eval_loss": 0.6951221227645874,
+      "eval_runtime": 0.11,
+      "eval_samples_per_second": 2518.222,
+      "eval_steps_per_second": 18.182,
+      "step": 10
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.6818793416023254,
+      "learning_rate": 4.8e-05,
+      "loss": 0.684,
+      "step": 20
+    },
+    {
+      "epoch": 2.0,
+      "eval_accuracy": 0.49458483754512633,
+      "eval_loss": 0.7016090154647827,
+      "eval_runtime": 0.1147,
+      "eval_samples_per_second": 2414.683,
+      "eval_steps_per_second": 17.435,
+      "step": 20
+    },
+    {
+      "epoch": 3.0,
+      "grad_norm": 0.6151508092880249,
+      "learning_rate": 4.7e-05,
+      "loss": 0.6682,
+      "step": 30
+    },
+    {
+      "epoch": 3.0,
+      "eval_accuracy": 0.5018050541516246,
+      "eval_loss": 0.7009462714195251,
+      "eval_runtime": 0.1166,
+      "eval_samples_per_second": 2376.571,
+      "eval_steps_per_second": 17.159,
+      "step": 30
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.5758317708969116,
+      "learning_rate": 4.600000000000001e-05,
+      "loss": 0.6498,
+      "step": 40
+    },
+    {
+      "epoch": 4.0,
+      "eval_accuracy": 0.48736462093862815,
+      "eval_loss": 0.7171741127967834,
+      "eval_runtime": 0.143,
+      "eval_samples_per_second": 1937.287,
+      "eval_steps_per_second": 13.988,
+      "step": 40
+    },
+    {
+      "epoch": 5.0,
+      "grad_norm": 0.9044778943061829,
+      "learning_rate": 4.5e-05,
+      "loss": 0.6256,
+      "step": 50
+    },
+    {
+      "epoch": 5.0,
+      "eval_accuracy": 0.5126353790613718,
+      "eval_loss": 0.7283922433853149,
+      "eval_runtime": 0.1117,
+      "eval_samples_per_second": 2479.088,
+      "eval_steps_per_second": 17.9,
+      "step": 50
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 0.8710564374923706,
+      "learning_rate": 4.4000000000000006e-05,
+      "loss": 0.5891,
+      "step": 60
+    },
+    {
+      "epoch": 6.0,
+      "eval_accuracy": 0.5054151624548736,
+      "eval_loss": 0.7591274380683899,
+      "eval_runtime": 0.1101,
+      "eval_samples_per_second": 2516.177,
+      "eval_steps_per_second": 18.167,
+      "step": 60
+    },
+    {
+      "epoch": 6.0,
+      "step": 60,
+      "total_flos": 391780256993280.0,
+      "train_loss": 0.6523992617925009,
+      "train_runtime": 15.3656,
+      "train_samples_per_second": 8102.502,
+      "train_steps_per_second": 32.54
+    }
+  ],
+  "logging_steps": 1,
+  "max_steps": 500,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 50,
+  "save_steps": 500,
+  "total_flos": 391780256993280.0,
+  "train_batch_size": 256,
+  "trial_name": null,
+  "trial_params": null
+}