---
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