README.md

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

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: 0.7029
- Accuracy: 0.5
- F1: 0.3333
- Precision: 0.25
- Recall: 0.5

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6983        | 1.0   | 48000  | 0.7029          | 0.5      | 0.3333 | 0.25      | 0.5    |
| 0.7189        | 2.0   | 96000  | 0.7414          | 0.5      | 0.3333 | 0.25      | 0.5    |
| 0.5927        | 3.0   | 144000 | 0.7370          | 0.5      | 0.3333 | 0.25      | 0.5    |
| 0.6274        | 4.0   | 192000 | 0.7668          | 0.5      | 0.3333 | 0.25      | 0.5    |
| 0.6622        | 5.0   | 240000 | 0.7478          | 0.5      | 0.3333 | 0.25      | 0.5    |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2