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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: mental/mental-roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- accuracy |
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model-index: |
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- name: mental-roberta-base-pr |
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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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# mental-roberta-base-pr |
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This model is a fine-tuned version of [mental/mental-roberta-base](https://huggingface.co/mental/mental-roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9572 |
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- F1 Macro: 0.6108 |
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- Precision: 0.6110 |
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- Recall: 0.6208 |
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- Accuracy: 0.7680 |
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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: 32 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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_ratio: 0.1 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro | Precision | Recall | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
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| No log | 1.0 | 240 | 2.2241 | 0.3643 | 0.4572 | 0.4376 | 0.5114 | |
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| No log | 2.0 | 480 | 0.8042 | 0.5883 | 0.5912 | 0.6185 | 0.7503 | |
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| 1.9047 | 3.0 | 720 | 0.7581 | 0.6197 | 0.6225 | 0.6376 | 0.7669 | |
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| 1.9047 | 4.0 | 960 | 0.7754 | 0.6211 | 0.6171 | 0.6381 | 0.7643 | |
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| 0.8579 | 5.0 | 1200 | 0.8229 | 0.6184 | 0.6299 | 0.6292 | 0.7695 | |
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| 0.8579 | 6.0 | 1440 | 0.9572 | 0.6108 | 0.6110 | 0.6208 | 0.7680 | |
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### Framework versions |
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- Transformers 4.57.1 |
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- Pytorch 2.8.0+cu128 |
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- Datasets 4.4.1 |
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- Tokenizers 0.22.1 |
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