End of training

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+model-index:
+- name: roberta-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: 0.930045871559633
+---
+
+<!-- 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. -->
+
+# roberta-sst2-distilled
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2485
+- Accuracy: 0.9300
+
+## 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: 6e-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: 7
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.257         | 1.0   | 527  | 0.2575          | 0.9117   |
+| 0.2386        | 2.0   | 1054 | 0.2469          | 0.9369   |
+| 0.2331        | 3.0   | 1581 | 0.2484          | 0.9358   |
+| 0.2289        | 4.0   | 2108 | 0.2516          | 0.9278   |
+| 0.2266        | 5.0   | 2635 | 0.2499          | 0.9335   |
+| 0.2252        | 6.0   | 3162 | 0.2477          | 0.9312   |
+| 0.2238        | 7.0   | 3689 | 0.2485          | 0.9300   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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