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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - glue
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: bert-mini-sst2-distilled
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: glue
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+ type: glue
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+ args: sst2
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.856651376146789
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # bert-mini-sst2-distilled
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+
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+ This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the glue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1792
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+ - Accuracy: 0.8567
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.00021185586235152412
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+ - train_batch_size: 1024
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+ - eval_batch_size: 1024
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+ - seed: 33
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 8
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.1552 | 1.0 | 66 | 1.4847 | 0.8349 |
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+ | 0.8451 | 2.0 | 132 | 1.3495 | 0.8624 |
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+ | 0.5864 | 3.0 | 198 | 1.2257 | 0.8532 |
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+ | 0.4553 | 4.0 | 264 | 1.2571 | 0.8544 |
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+ | 0.3708 | 5.0 | 330 | 1.2132 | 0.8658 |
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+ | 0.3086 | 6.0 | 396 | 1.2370 | 0.8589 |
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+ | 0.2701 | 7.0 | 462 | 1.1900 | 0.8635 |
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+ | 0.246 | 8.0 | 528 | 1.1792 | 0.8567 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.12.3
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+ - Pytorch 1.9.1
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+ - Datasets 1.15.1
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+ - Tokenizers 0.10.3
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