End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+- f1
+- matthews_correlation
+model-index:
+- name: bert-base-uncased-finetuned-glue_cola
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      config: cola
+      split: validation
+      args: cola
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8293384467881112
+    - name: F1
+      type: f1
+      value: 0.820234272230632
+    - name: Matthews Correlation
+      type: matthews_correlation
+      value: 0.5806473000395166
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bert-base-uncased-finetuned-glue_cola
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6466
+- Accuracy: 0.8293
+- F1: 0.8202
+- Matthews Correlation: 0.5806
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Matthews Correlation |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------------:|
+| 0.5418        | 1.0   | 535  | 0.4594          | 0.8006   | 0.7836 | 0.5019               |
+| 0.3635        | 2.0   | 1070 | 0.4437          | 0.8217   | 0.8084 | 0.5600               |
+| 0.2019        | 3.0   | 1605 | 0.6466          | 0.8293   | 0.8202 | 0.5806               |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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