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--- |
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library_name: transformers |
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license: mit |
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base_model: FacebookAI/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: FacebookAI_roberta-large_custom_data |
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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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# FacebookAI_roberta-large_custom_data |
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This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3779 |
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- Precision Macro: 0.8141 |
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- Recall Macro: 0.8170 |
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- F1 Macro: 0.8155 |
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- Accuracy: 0.8117 |
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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: 16 |
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- eval_batch_size: 16 |
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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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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision Macro | Recall Macro | F1 Macro | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------:|:--------:| |
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| 0.5113 | 1.0 | 270 | 0.3779 | 0.8141 | 0.8170 | 0.8155 | 0.8117 | |
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| 0.3962 | 2.0 | 540 | 0.4214 | 0.8266 | 0.8093 | 0.8125 | 0.8200 | |
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| 0.2556 | 3.0 | 810 | 0.4619 | 0.8149 | 0.8106 | 0.8112 | 0.8135 | |
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### Framework versions |
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- Transformers 4.48.0 |
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- Pytorch 2.5.1 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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