---
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-base-CD_baseline
  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-CD_baseline

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: 1.2770
- Accuracy: 0.5957
- F1: 0.5795
- Precision: 0.5801
- Recall: 0.5957

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.7629        | 1.0   | 250  | 1.5328          | 0.4739   | 0.3843 | 0.3535    | 0.4739 |
| 1.4033        | 2.0   | 500  | 1.3282          | 0.5261   | 0.5010 | 0.5395    | 0.5261 |
| 0.7635        | 3.0   | 750  | 1.3102          | 0.5609   | 0.5337 | 0.5372    | 0.5609 |
| 0.8688        | 4.0   | 1000 | 1.2770          | 0.5957   | 0.5795 | 0.5801    | 0.5957 |
| 0.4432        | 5.0   | 1250 | 1.4374          | 0.6087   | 0.5941 | 0.6038    | 0.6087 |
| 0.3489        | 6.0   | 1500 | 1.4813          | 0.5870   | 0.5901 | 0.6124    | 0.5870 |
| 0.3154        | 7.0   | 1750 | 1.5613          | 0.5913   | 0.5923 | 0.6051    | 0.5913 |
| 0.1553        | 8.0   | 2000 | 1.6126          | 0.5957   | 0.5931 | 0.5986    | 0.5957 |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.15.2