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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-2-64-13-30 |
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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-2-64-13-30 |
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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: 0.6400 |
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- Accuracy: 0.8984 |
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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 | 4 | 0.6936 | 0.5 | |
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| No log | 2.0 | 8 | 0.6928 | 0.5156 | |
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| 0.6938 | 3.0 | 12 | 0.6921 | 0.6328 | |
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| 0.6938 | 4.0 | 16 | 0.6911 | 0.6328 | |
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| 0.6895 | 5.0 | 20 | 0.6894 | 0.5859 | |
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| 0.6895 | 6.0 | 24 | 0.6866 | 0.625 | |
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| 0.6895 | 7.0 | 28 | 0.6818 | 0.6641 | |
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| 0.6758 | 8.0 | 32 | 0.6727 | 0.6953 | |
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| 0.6758 | 9.0 | 36 | 0.6495 | 0.7656 | |
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| 0.615 | 10.0 | 40 | 0.5773 | 0.8125 | |
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| 0.615 | 11.0 | 44 | 0.4229 | 0.875 | |
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| 0.615 | 12.0 | 48 | 0.3311 | 0.8906 | |
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| 0.3514 | 13.0 | 52 | 0.3047 | 0.8906 | |
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| 0.3514 | 14.0 | 56 | 0.3420 | 0.8828 | |
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| 0.0929 | 15.0 | 60 | 0.4113 | 0.8906 | |
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| 0.0929 | 16.0 | 64 | 0.4550 | 0.8906 | |
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| 0.0929 | 17.0 | 68 | 0.5299 | 0.8906 | |
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| 0.0206 | 18.0 | 72 | 0.6554 | 0.8594 | |
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| 0.0206 | 19.0 | 76 | 0.7213 | 0.8594 | |
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| 0.007 | 20.0 | 80 | 0.7860 | 0.8516 | |
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| 0.007 | 21.0 | 84 | 0.8466 | 0.8438 | |
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| 0.007 | 22.0 | 88 | 0.8522 | 0.8516 | |
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| 0.0037 | 23.0 | 92 | 0.8023 | 0.8516 | |
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| 0.0037 | 24.0 | 96 | 0.6670 | 0.8828 | |
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| 0.0028 | 25.0 | 100 | 0.6224 | 0.8984 | |
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| 0.0028 | 26.0 | 104 | 0.6283 | 0.8906 | |
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| 0.0028 | 27.0 | 108 | 0.6333 | 0.8906 | |
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| 0.0026 | 28.0 | 112 | 0.6307 | 0.8906 | |
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| 0.0026 | 29.0 | 116 | 0.6348 | 0.8984 | |
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| 0.003 | 30.0 | 120 | 0.6400 | 0.8984 | |
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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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