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library_name: transformers
license: cc-by-nc-4.0
base_model: mental/mental-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: mental-roberta-base-pr
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mental-roberta-base-pr
This model is a fine-tuned version of [mental/mental-roberta-base](https://huggingface.co/mental/mental-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9572
- F1 Macro: 0.6108
- Precision: 0.6110
- Recall: 0.6208
- Accuracy: 0.7680
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | Precision | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| No log | 1.0 | 240 | 2.2241 | 0.3643 | 0.4572 | 0.4376 | 0.5114 |
| No log | 2.0 | 480 | 0.8042 | 0.5883 | 0.5912 | 0.6185 | 0.7503 |
| 1.9047 | 3.0 | 720 | 0.7581 | 0.6197 | 0.6225 | 0.6376 | 0.7669 |
| 1.9047 | 4.0 | 960 | 0.7754 | 0.6211 | 0.6171 | 0.6381 | 0.7643 |
| 0.8579 | 5.0 | 1200 | 0.8229 | 0.6184 | 0.6299 | 0.6292 | 0.7695 |
| 0.8579 | 6.0 | 1440 | 0.9572 | 0.6108 | 0.6110 | 0.6208 | 0.7680 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1
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