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--- |
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license: mit |
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base_model: roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: roberta-base-sst-2-32-13-30 |
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results: [] |
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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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# roberta-base-sst-2-32-13-30 |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5496 |
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- Accuracy: 0.75 |
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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: 1.5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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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- lr_scheduler_warmup_steps: 5 |
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- num_epochs: 30 |
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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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| No log | 1.0 | 2 | 0.6930 | 0.5156 | |
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| No log | 2.0 | 4 | 0.6929 | 0.5 | |
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| No log | 3.0 | 6 | 0.6928 | 0.5 | |
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| No log | 4.0 | 8 | 0.6925 | 0.5 | |
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| 0.6955 | 5.0 | 10 | 0.6920 | 0.5 | |
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| 0.6955 | 6.0 | 12 | 0.6914 | 0.5156 | |
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| 0.6955 | 7.0 | 14 | 0.6904 | 0.5469 | |
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| 0.6955 | 8.0 | 16 | 0.6891 | 0.5312 | |
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| 0.6955 | 9.0 | 18 | 0.6872 | 0.5156 | |
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| 0.6791 | 10.0 | 20 | 0.6845 | 0.5312 | |
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| 0.6791 | 11.0 | 22 | 0.6805 | 0.5312 | |
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| 0.6791 | 12.0 | 24 | 0.6751 | 0.5312 | |
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| 0.6791 | 13.0 | 26 | 0.6654 | 0.5625 | |
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| 0.6791 | 14.0 | 28 | 0.6525 | 0.625 | |
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| 0.6052 | 15.0 | 30 | 0.6347 | 0.6406 | |
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| 0.6052 | 16.0 | 32 | 0.6130 | 0.6719 | |
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| 0.6052 | 17.0 | 34 | 0.5903 | 0.6875 | |
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| 0.6052 | 18.0 | 36 | 0.5770 | 0.6875 | |
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| 0.6052 | 19.0 | 38 | 0.5569 | 0.7031 | |
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| 0.3501 | 20.0 | 40 | 0.5333 | 0.75 | |
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| 0.3501 | 21.0 | 42 | 0.5251 | 0.7344 | |
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| 0.3501 | 22.0 | 44 | 0.5137 | 0.75 | |
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| 0.3501 | 23.0 | 46 | 0.5118 | 0.7656 | |
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| 0.3501 | 24.0 | 48 | 0.5151 | 0.7656 | |
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| 0.137 | 25.0 | 50 | 0.5202 | 0.7656 | |
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| 0.137 | 26.0 | 52 | 0.5299 | 0.7656 | |
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| 0.137 | 27.0 | 54 | 0.5379 | 0.7656 | |
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| 0.137 | 28.0 | 56 | 0.5433 | 0.75 | |
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| 0.137 | 29.0 | 58 | 0.5477 | 0.75 | |
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| 0.0715 | 30.0 | 60 | 0.5496 | 0.75 | |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.4.0 |
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- Tokenizers 0.13.3 |
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