End of training

README.md

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+---
+license: apache-2.0
+base_model: google/bert_uncased_L-2_H-128_A-2
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+model-index:
+- name: tiny-bert-sst2-distilled
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      config: sst2
+      split: validation
+      args: sst2
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7947247706422018
+---
+
+<!-- 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. -->
+
+# tiny-bert-sst2-distilled
+
+This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6692
+- Accuracy: 0.7947
+
+## 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: 4.787209189533254e-05
+- train_batch_size: 128
+- eval_batch_size: 128
+- seed: 33
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.4226        | 1.0   | 527  | 1.7918          | 0.7844   |
+| 1.5656        | 2.0   | 1054 | 1.6692          | 0.7947   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.7
+- Tokenizers 0.15.0

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