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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_sst2_padding50model |
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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_sst2_padding50model |
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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: 0.5107 |
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- Accuracy: 0.9462 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- num_epochs: 20 |
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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 | 433 | 0.1735 | 0.9319 | |
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| 0.327 | 2.0 | 866 | 0.2500 | 0.9336 | |
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| 0.1893 | 3.0 | 1299 | 0.2987 | 0.9407 | |
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| 0.1229 | 4.0 | 1732 | 0.3376 | 0.9418 | |
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| 0.0753 | 5.0 | 2165 | 0.3283 | 0.9484 | |
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| 0.0496 | 6.0 | 2598 | 0.5720 | 0.9116 | |
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| 0.0349 | 7.0 | 3031 | 0.4278 | 0.9363 | |
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| 0.0349 | 8.0 | 3464 | 0.4501 | 0.9379 | |
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| 0.0254 | 9.0 | 3897 | 0.4728 | 0.9374 | |
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| 0.0217 | 10.0 | 4330 | 0.4662 | 0.9368 | |
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| 0.0171 | 11.0 | 4763 | 0.4622 | 0.9418 | |
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| 0.0082 | 12.0 | 5196 | 0.4804 | 0.9429 | |
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| 0.0094 | 13.0 | 5629 | 0.4789 | 0.9445 | |
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| 0.0047 | 14.0 | 6062 | 0.5459 | 0.9423 | |
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| 0.0047 | 15.0 | 6495 | 0.4672 | 0.9434 | |
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| 0.009 | 16.0 | 6928 | 0.5178 | 0.9445 | |
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| 0.0021 | 17.0 | 7361 | 0.5107 | 0.9467 | |
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| 0.0042 | 18.0 | 7794 | 0.5101 | 0.9445 | |
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| 0.0053 | 19.0 | 8227 | 0.5043 | 0.9462 | |
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| 0.0017 | 20.0 | 8660 | 0.5107 | 0.9462 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.1 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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