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--- |
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license: mit |
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base_model: FacebookAI/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: STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-170 |
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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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# STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-170 |
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This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3403 |
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- Accuracy: 0.7285 |
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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: 3e-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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- 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 | 113 | 0.7529 | 0.6816 | |
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| No log | 2.0 | 226 | 0.7985 | 0.7097 | |
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| No log | 3.0 | 339 | 0.8245 | 0.7097 | |
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| No log | 4.0 | 452 | 0.8816 | 0.6798 | |
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| 0.5011 | 5.0 | 565 | 1.0854 | 0.6929 | |
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| 0.5011 | 6.0 | 678 | 1.1921 | 0.7135 | |
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| 0.5011 | 7.0 | 791 | 1.3839 | 0.7228 | |
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| 0.5011 | 8.0 | 904 | 1.4560 | 0.7247 | |
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| 0.1649 | 9.0 | 1017 | 1.6387 | 0.7191 | |
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| 0.1649 | 10.0 | 1130 | 1.8012 | 0.7172 | |
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| 0.1649 | 11.0 | 1243 | 1.8790 | 0.7247 | |
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| 0.1649 | 12.0 | 1356 | 2.0223 | 0.7116 | |
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| 0.1649 | 13.0 | 1469 | 2.0297 | 0.7228 | |
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| 0.0639 | 14.0 | 1582 | 2.1202 | 0.7228 | |
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| 0.0639 | 15.0 | 1695 | 2.2489 | 0.7303 | |
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| 0.0639 | 16.0 | 1808 | 2.2505 | 0.7266 | |
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| 0.0639 | 17.0 | 1921 | 2.2693 | 0.7303 | |
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| 0.0198 | 18.0 | 2034 | 2.3216 | 0.7228 | |
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| 0.0198 | 19.0 | 2147 | 2.3244 | 0.7247 | |
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| 0.0198 | 20.0 | 2260 | 2.3403 | 0.7285 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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