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--- |
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library_name: transformers |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: roberta-stance |
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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-stance |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1034 |
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- Accuracy: 0.6232 |
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- Precision: 0.6077 |
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- Recall: 0.6301 |
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- F1: 0.6127 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 46 | 1.0695 | 0.5184 | 0.1728 | 0.3333 | 0.2276 | |
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| No log | 2.0 | 92 | 1.0372 | 0.5184 | 0.1728 | 0.3333 | 0.2276 | |
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| No log | 3.0 | 138 | 0.9757 | 0.5746 | 0.4121 | 0.4214 | 0.3711 | |
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| No log | 4.0 | 184 | 0.8826 | 0.6063 | 0.5820 | 0.5298 | 0.5423 | |
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| No log | 5.0 | 230 | 0.8429 | 0.6166 | 0.6159 | 0.6011 | 0.5824 | |
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| No log | 6.0 | 276 | 0.8153 | 0.6472 | 0.6257 | 0.6376 | 0.6294 | |
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| No log | 7.0 | 322 | 0.8600 | 0.6559 | 0.6492 | 0.6427 | 0.6315 | |
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| No log | 8.0 | 368 | 0.8912 | 0.6299 | 0.6138 | 0.6159 | 0.6108 | |
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| No log | 9.0 | 414 | 1.0091 | 0.6161 | 0.6048 | 0.6345 | 0.6084 | |
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| No log | 10.0 | 460 | 1.1034 | 0.6232 | 0.6077 | 0.6301 | 0.6127 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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