---
license: cc-by-nc-4.0
base_model: mental/mental-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [mental/mental-roberta-base](https://huggingface.co/mental/mental-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7715
- Accuracy: 0.8014
- F1: 0.8161
- Precision: 0.7816
- Recall: 0.8537

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3921        | 0.99  | 31   | 0.4379          | 0.8042   | 0.8153 | 0.7943    | 0.8374 |
| 0.3376        | 1.98  | 62   | 0.4358          | 0.8112   | 0.8173 | 0.8162    | 0.8184 |
| 0.3126        | 2.98  | 93   | 0.4642          | 0.7972   | 0.8172 | 0.7642    | 0.8780 |
| 0.2838        | 4.0   | 125  | 0.4438          | 0.8196   | 0.8264 | 0.8209    | 0.8320 |
| 0.2504        | 4.99  | 156  | 0.5249          | 0.7958   | 0.8161 | 0.7624    | 0.8780 |
| 0.2912        | 5.98  | 187  | 0.6067          | 0.7972   | 0.8221 | 0.7511    | 0.9079 |
| 0.1335        | 6.98  | 218  | 0.7014          | 0.8      | 0.8197 | 0.7665    | 0.8808 |
| 0.1579        | 7.94  | 248  | 0.7715          | 0.8014   | 0.8161 | 0.7816    | 0.8537 |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2