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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: tiny-bert-sst2-distilled-model |
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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: 0.838302752293578 |
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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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# tiny-bert-sst2-distilled-model |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2592 |
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- Accuracy: 0.8383 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 6e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 7 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 0.5303 | 1.0 | 4210 | 1.2542 | 0.8222 | |
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| 0.4503 | 2.0 | 8420 | 1.1260 | 0.8211 | |
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| 0.3689 | 3.0 | 12630 | 1.2325 | 0.8234 | |
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| 0.3122 | 4.0 | 16840 | 1.2533 | 0.8337 | |
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| 0.2764 | 5.0 | 21050 | 1.2726 | 0.8337 | |
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| 0.254 | 6.0 | 25260 | 1.2609 | 0.8337 | |
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| 0.2358 | 7.0 | 29470 | 1.2592 | 0.8383 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.10.1+cu113 |
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- Datasets 1.15.1 |
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- Tokenizers 0.12.1 |
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