End of training

README.md

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+---
+license: apache-2.0
+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
+      args: sst2
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8325688073394495
+---
+
+<!-- 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: 1.7305
+- Accuracy: 0.8326
+
+## 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: 0.0007199555649276667
+- train_batch_size: 1024
+- eval_batch_size: 1024
+- seed: 33
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 7
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.77          | 1.0   | 66   | 1.6939          | 0.8165   |
+| 0.729         | 2.0   | 132  | 1.5090          | 0.8326   |
+| 0.5242        | 3.0   | 198  | 1.5369          | 0.8257   |
+| 0.4017        | 4.0   | 264  | 1.7025          | 0.8326   |
+| 0.327         | 5.0   | 330  | 1.6743          | 0.8245   |
+| 0.2749        | 6.0   | 396  | 1.7305          | 0.8337   |
+| 0.2521        | 7.0   | 462  | 1.7305          | 0.8326   |
+
+
+### Framework versions
+
+- Transformers 4.12.3
+- Pytorch 1.9.1
+- Datasets 1.15.1
+- Tokenizers 0.10.3

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