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--- |
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base_model: distilbert/distilroberta-base |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: my_model |
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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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# my_model |
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This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7996 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 45 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 1.0 | 199 | 1.7128 | |
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| No log | 2.0 | 398 | 1.4856 | |
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| 1.8719 | 3.0 | 597 | 1.3661 | |
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| 1.8719 | 4.0 | 796 | 1.2638 | |
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| 1.8719 | 5.0 | 995 | 1.1847 | |
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| 1.3663 | 6.0 | 1194 | 1.1849 | |
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| 1.3663 | 7.0 | 1393 | 1.1757 | |
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| 1.2108 | 8.0 | 1592 | 1.1026 | |
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| 1.2108 | 9.0 | 1791 | 1.0826 | |
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| 1.2108 | 10.0 | 1990 | 1.0609 | |
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| 1.1079 | 11.0 | 2189 | 1.0221 | |
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| 1.1079 | 12.0 | 2388 | 1.0199 | |
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| 1.0428 | 13.0 | 2587 | 0.9990 | |
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| 1.0428 | 14.0 | 2786 | 1.0083 | |
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| 1.0428 | 15.0 | 2985 | 0.9905 | |
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| 0.9911 | 16.0 | 3184 | 0.9492 | |
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| 0.9911 | 17.0 | 3383 | 0.9526 | |
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| 0.9391 | 18.0 | 3582 | 0.9219 | |
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| 0.9391 | 19.0 | 3781 | 0.9228 | |
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| 0.9391 | 20.0 | 3980 | 0.9183 | |
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| 0.9078 | 21.0 | 4179 | 0.9276 | |
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| 0.9078 | 22.0 | 4378 | 0.8874 | |
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| 0.8727 | 23.0 | 4577 | 0.8856 | |
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| 0.8727 | 24.0 | 4776 | 0.8899 | |
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| 0.8727 | 25.0 | 4975 | 0.8836 | |
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| 0.8513 | 26.0 | 5174 | 0.8790 | |
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| 0.8513 | 27.0 | 5373 | 0.8835 | |
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| 0.8145 | 28.0 | 5572 | 0.8583 | |
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| 0.8145 | 29.0 | 5771 | 0.8498 | |
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| 0.8145 | 30.0 | 5970 | 0.8530 | |
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| 0.8085 | 31.0 | 6169 | 0.8409 | |
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| 0.8085 | 32.0 | 6368 | 0.8196 | |
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| 0.7783 | 33.0 | 6567 | 0.8311 | |
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| 0.7783 | 34.0 | 6766 | 0.8301 | |
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| 0.7783 | 35.0 | 6965 | 0.8370 | |
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| 0.7639 | 36.0 | 7164 | 0.8321 | |
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| 0.7639 | 37.0 | 7363 | 0.8226 | |
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| 0.757 | 38.0 | 7562 | 0.8361 | |
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| 0.757 | 39.0 | 7761 | 0.8236 | |
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| 0.757 | 40.0 | 7960 | 0.8255 | |
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| 0.7483 | 41.0 | 8159 | 0.8305 | |
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| 0.7483 | 42.0 | 8358 | 0.8057 | |
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| 0.7449 | 43.0 | 8557 | 0.8251 | |
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| 0.7449 | 44.0 | 8756 | 0.8014 | |
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| 0.7449 | 45.0 | 8955 | 0.7996 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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