End of training

README.md

@@ -1,12 +1,27 @@
 ---
+language:
+- en
 base_model: Hartunka/tiny_bert_km_100_v1
 tags:
 - generated_from_trainer
+datasets:
+- glue
 metrics:
 - accuracy
 model-index:
 - name: tiny_bert_km_100_v1_wnli
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: GLUE WNLI
+      type: glue
+      args: wnli
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.5211267605633803
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -14,10 +29,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # tiny_bert_km_100_v1_wnli
 
-This model is a fine-tuned version of [Hartunka/tiny_bert_km_100_v1](https://huggingface.co/Hartunka/tiny_bert_km_100_v1) on an unknown dataset.
+This model is a fine-tuned version of [Hartunka/tiny_bert_km_100_v1](https://huggingface.co/Hartunka/tiny_bert_km_100_v1) on the GLUE WNLI dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7314
-- Accuracy: 0.3803
+- Loss: 0.6931
+- Accuracy: 0.5211
 
 ## Model description
 

all_results.json

@@ -0,0 +1,15 @@
+{
+    "epoch": 6.0,
+    "eval_accuracy": 0.5211267605633803,
+    "eval_loss": 0.6930568218231201,
+    "eval_runtime": 0.0598,
+    "eval_samples": 71,
+    "eval_samples_per_second": 1188.07,
+    "eval_steps_per_second": 16.733,
+    "total_flos": 99911832606720.0,
+    "train_loss": 0.6949052943123711,
+    "train_runtime": 8.1637,
+    "train_samples": 635,
+    "train_samples_per_second": 3889.17,
+    "train_steps_per_second": 18.374
+}

eval_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 6.0,
+    "eval_accuracy": 0.5211267605633803,
+    "eval_loss": 0.6930568218231201,
+    "eval_runtime": 0.0598,
+    "eval_samples": 71,
+    "eval_samples_per_second": 1188.07,
+    "eval_steps_per_second": 16.733
+}

logs/events.out.tfevents.1744821368.s_004_m

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2491c28887f30d8c6c7e0bb2790309aeaefe238bb92cb2eb03b40d208150dfae
+size 249

train_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 6.0,
+    "total_flos": 99911832606720.0,
+    "train_loss": 0.6949052943123711,
+    "train_runtime": 8.1637,
+    "train_samples": 635,
+    "train_samples_per_second": 3889.17,
+    "train_steps_per_second": 18.374
+}

trainer_state.json

@@ -0,0 +1,126 @@
+{
+  "best_metric": 0.6930568218231201,
+  "best_model_checkpoint": "tiny_bert_km_100_v1_wnli/checkpoint-3",
+  "epoch": 6.0,
+  "eval_steps": 500,
+  "global_step": 18,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 1.0,
+      "grad_norm": 0.8802371621131897,
+      "learning_rate": 4.9e-05,
+      "loss": 0.7061,
+      "step": 3
+    },
+    {
+      "epoch": 1.0,
+      "eval_accuracy": 0.5211267605633803,
+      "eval_loss": 0.6930568218231201,
+      "eval_runtime": 0.0372,
+      "eval_samples_per_second": 1907.54,
+      "eval_steps_per_second": 26.867,
+      "step": 3
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7727060914039612,
+      "learning_rate": 4.8e-05,
+      "loss": 0.6931,
+      "step": 6
+    },
+    {
+      "epoch": 2.0,
+      "eval_accuracy": 0.49295774647887325,
+      "eval_loss": 0.6975681781768799,
+      "eval_runtime": 0.0365,
+      "eval_samples_per_second": 1946.16,
+      "eval_steps_per_second": 27.411,
+      "step": 6
+    },
+    {
+      "epoch": 3.0,
+      "grad_norm": 0.6414340138435364,
+      "learning_rate": 4.7e-05,
+      "loss": 0.6991,
+      "step": 9
+    },
+    {
+      "epoch": 3.0,
+      "eval_accuracy": 0.38028169014084506,
+      "eval_loss": 0.7135781645774841,
+      "eval_runtime": 0.0381,
+      "eval_samples_per_second": 1861.106,
+      "eval_steps_per_second": 26.213,
+      "step": 9
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.7113948464393616,
+      "learning_rate": 4.600000000000001e-05,
+      "loss": 0.692,
+      "step": 12
+    },
+    {
+      "epoch": 4.0,
+      "eval_accuracy": 0.38028169014084506,
+      "eval_loss": 0.719905436038971,
+      "eval_runtime": 0.0377,
+      "eval_samples_per_second": 1882.983,
+      "eval_steps_per_second": 26.521,
+      "step": 12
+    },
+    {
+      "epoch": 5.0,
+      "grad_norm": 0.803973913192749,
+      "learning_rate": 4.5e-05,
+      "loss": 0.6907,
+      "step": 15
+    },
+    {
+      "epoch": 5.0,
+      "eval_accuracy": 0.36619718309859156,
+      "eval_loss": 0.7242516279220581,
+      "eval_runtime": 0.0386,
+      "eval_samples_per_second": 1841.427,
+      "eval_steps_per_second": 25.936,
+      "step": 15
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 0.8193577527999878,
+      "learning_rate": 4.4000000000000006e-05,
+      "loss": 0.6884,
+      "step": 18
+    },
+    {
+      "epoch": 6.0,
+      "eval_accuracy": 0.38028169014084506,
+      "eval_loss": 0.7314040064811707,
+      "eval_runtime": 0.0412,
+      "eval_samples_per_second": 1722.527,
+      "eval_steps_per_second": 24.261,
+      "step": 18
+    },
+    {
+      "epoch": 6.0,
+      "step": 18,
+      "total_flos": 99911832606720.0,
+      "train_loss": 0.6949052943123711,
+      "train_runtime": 8.1637,
+      "train_samples_per_second": 3889.17,
+      "train_steps_per_second": 18.374
+    }
+  ],
+  "logging_steps": 1,
+  "max_steps": 150,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 50,
+  "save_steps": 500,
+  "total_flos": 99911832606720.0,
+  "train_batch_size": 256,
+  "trial_name": null,
+  "trial_params": null
+}