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results
This model is a fine-tuned version of mental/mental-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8954
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7819 | 1.0 | 1250 | 0.6605 |
| 0.6951 | 2.0 | 2500 | 0.6324 |
| 0.6588 | 3.0 | 3750 | 0.6552 |
| 0.6606 | 4.0 | 5000 | 0.6459 |
| 0.6204 | 5.0 | 6250 | 0.6616 |
| 0.5902 | 6.0 | 7500 | 0.6793 |
| 0.567 | 7.0 | 8750 | 0.6592 |
| 0.5452 | 8.0 | 10000 | 0.6582 |
| 0.5296 | 9.0 | 11250 | 0.6896 |
| 0.5073 | 10.0 | 12500 | 0.6497 |
| 0.4521 | 11.0 | 13750 | 0.6788 |
| 0.4289 | 12.0 | 15000 | 0.6858 |
| 0.3918 | 13.0 | 16250 | 0.6804 |
| 0.3683 | 14.0 | 17500 | 0.7224 |
| 0.3235 | 15.0 | 18750 | 0.7345 |
| 0.2884 | 16.0 | 20000 | 0.7899 |
| 0.2587 | 17.0 | 21250 | 0.8118 |
| 0.2296 | 18.0 | 22500 | 0.8464 |
| 0.1957 | 19.0 | 23750 | 0.8771 |
| 0.1702 | 20.0 | 25000 | 0.8954 |
Framework versions
- PEFT 0.17.1
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Base model
mental/mental-roberta-base