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--- |
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license: mit |
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base_model: roberta-large |
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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-large-sst-2-16-13-30 |
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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-large-sst-2-16-13-30 |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6901 |
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- Accuracy: 0.625 |
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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 | 1 | 0.6957 | 0.5 | |
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| No log | 2.0 | 2 | 0.6955 | 0.5 | |
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| No log | 3.0 | 3 | 0.6952 | 0.5 | |
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| No log | 4.0 | 4 | 0.6944 | 0.5 | |
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| No log | 5.0 | 5 | 0.6937 | 0.5 | |
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| No log | 6.0 | 6 | 0.6933 | 0.5 | |
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| No log | 7.0 | 7 | 0.6929 | 0.5 | |
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| No log | 8.0 | 8 | 0.6942 | 0.5 | |
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| No log | 9.0 | 9 | 0.6931 | 0.5 | |
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| 0.6903 | 10.0 | 10 | 0.6917 | 0.5 | |
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| 0.6903 | 11.0 | 11 | 0.6905 | 0.5 | |
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| 0.6903 | 12.0 | 12 | 0.6891 | 0.5312 | |
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| 0.6903 | 13.0 | 13 | 0.6883 | 0.625 | |
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| 0.6903 | 14.0 | 14 | 0.6874 | 0.6562 | |
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| 0.6903 | 15.0 | 15 | 0.6849 | 0.5312 | |
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| 0.6903 | 16.0 | 16 | 0.6822 | 0.5312 | |
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| 0.6903 | 17.0 | 17 | 0.6790 | 0.5 | |
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| 0.6903 | 18.0 | 18 | 0.6742 | 0.5 | |
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| 0.6903 | 19.0 | 19 | 0.6650 | 0.5312 | |
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| 0.626 | 20.0 | 20 | 0.6524 | 0.5312 | |
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| 0.626 | 21.0 | 21 | 0.6444 | 0.5312 | |
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| 0.626 | 22.0 | 22 | 0.6361 | 0.5625 | |
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| 0.626 | 23.0 | 23 | 0.6327 | 0.5938 | |
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| 0.626 | 24.0 | 24 | 0.6337 | 0.625 | |
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| 0.626 | 25.0 | 25 | 0.6437 | 0.625 | |
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| 0.626 | 26.0 | 26 | 0.6580 | 0.6562 | |
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| 0.626 | 27.0 | 27 | 0.6725 | 0.6562 | |
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| 0.626 | 28.0 | 28 | 0.6812 | 0.625 | |
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| 0.626 | 29.0 | 29 | 0.6873 | 0.625 | |
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| 0.4393 | 30.0 | 30 | 0.6901 | 0.625 | |
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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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