---
license: cc-by-nc-4.0
base_model: Zamoranesis/mental_bert
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: mental_bert_classifier
  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_bert_classifier

This model is a fine-tuned version of [Zamoranesis/mental_bert](https://huggingface.co/Zamoranesis/mental_bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3709
- F1 Class 0: 0.8475
- F1 Class 1: 0.9157
- F1 Class 2: 0.7692
- F1 Class 3: 0.8764
- F1 Class 4: 0.8772
- F1: 0.8572

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 100
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Class 0 | F1 Class 1 | F1 Class 2 | F1 Class 3 | F1 Class 4 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:----------:|:----------:|:----------:|:----------:|:------:|
| 1.3938        | 6.25  | 100  | 1.0235          | 0.7458     | 0.8000     | 0.6957     | 0.8315     | 0.8197     | 0.7785 |
| 0.7425        | 12.5  | 200  | 0.6302          | 0.7667     | 0.875      | 0.7755     | 0.8478     | 0.8475     | 0.8225 |
| 0.5225        | 18.75 | 300  | 0.5192          | 0.8276     | 0.9268     | 0.7843     | 0.8667     | 0.8475     | 0.8506 |
| 0.4433        | 25.0  | 400  | 0.4599          | 0.8276     | 0.9157     | 0.7692     | 0.8636     | 0.8475     | 0.8447 |
| 0.3862        | 31.25 | 500  | 0.4208          | 0.8475     | 0.9157     | 0.7692     | 0.8636     | 0.8621     | 0.8516 |
| 0.3702        | 37.5  | 600  | 0.3987          | 0.8475     | 0.9157     | 0.7692     | 0.8764     | 0.8772     | 0.8572 |
| 0.3437        | 43.75 | 700  | 0.3872          | 0.8475     | 0.9157     | 0.7692     | 0.8764     | 0.8772     | 0.8572 |
| 0.337         | 50.0  | 800  | 0.3759          | 0.8475     | 0.9157     | 0.7692     | 0.8764     | 0.8772     | 0.8572 |
| 0.3253        | 56.25 | 900  | 0.3727          | 0.8475     | 0.9157     | 0.7692     | 0.8764     | 0.8772     | 0.8572 |
| 0.3236        | 62.5  | 1000 | 0.3709          | 0.8475     | 0.9157     | 0.7692     | 0.8764     | 0.8772     | 0.8572 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3