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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: AIMH/mental-roberta-large |
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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-large-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-large-pr |
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This model is a fine-tuned version of [AIMH/mental-roberta-large](https://huggingface.co/AIMH/mental-roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3882 |
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- F1 Macro: 0.6298 |
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- Precision: 0.6338 |
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- Recall: 0.6393 |
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- Accuracy: 0.7836 |
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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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- mixed_precision_training: Native AMP |
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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 | 1.3410 | 0.5133 | 0.5270 | 0.5471 | 0.6894 | |
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| No log | 2.0 | 480 | 0.8069 | 0.6099 | 0.5990 | 0.6440 | 0.7445 | |
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| 1.75 | 3.0 | 720 | 0.7779 | 0.6290 | 0.6333 | 0.6492 | 0.7752 | |
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| 1.75 | 4.0 | 960 | 0.8297 | 0.6240 | 0.6311 | 0.6390 | 0.7804 | |
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| 0.6742 | 5.0 | 1200 | 1.0208 | 0.6312 | 0.6295 | 0.6439 | 0.7737 | |
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| 0.6742 | 6.0 | 1440 | 1.1990 | 0.6294 | 0.6374 | 0.6384 | 0.7804 | |
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| 0.2441 | 7.0 | 1680 | 1.3882 | 0.6298 | 0.6338 | 0.6393 | 0.7836 | |
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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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