---
license: cc-by-nc-4.0
base_model: Zamoranesis/mental_bert
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: mental_bert_classifier
  results: []
widget: The person seems obsessed with the signals he receives from the environment, always looking for hidden meanings behind the words and actions of others.
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mental_bert_classifier

This model is a fine-tuned version of [Zamoranesis/mental_bert](https://huggingface.co/Zamoranesis/mental_bert) on [hackathon-somos-nlp-2023/DiagTrast](https://huggingface.co/datasets/hackathon-somos-nlp-2023/DiagTrast).
It achieves the following results on the evaluation set:
- Loss: 0.2426
- F1 Class 0: 0.8852
- F1 Class 1: 0.9512
- F1 Class 2: 0.8421
- F1 Class 3: 0.8539
- F1 Class 4: 0.9412
- F1: 0.8947

## 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: 0.005
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:----------:|:----------:|:----------:|:----------:|:------:|
| 0.7979        | 6.25  | 100  | 0.3557          | 0.8421     | 0.9512     | 0.8214     | 0.8889     | 0.9091     | 0.8825 |
| 0.2559        | 12.5  | 200  | 0.2823          | 0.9333     | 0.9412     | 0.8364     | 0.8602     | 0.9362     | 0.9015 |
| 0.1963        | 18.75 | 300  | 0.2610          | 0.9180     | 0.9756     | 0.7778     | 0.8352     | 0.9231     | 0.8859 |
| 0.1717        | 25.0  | 400  | 0.2534          | 0.9180     | 0.9630     | 0.8        | 0.8261     | 0.9412     | 0.8897 |
| 0.1511        | 31.25 | 500  | 0.2476          | 0.8667     | 0.9512     | 0.8148     | 0.8298     | 0.96       | 0.8845 |
| 0.1501        | 37.5  | 600  | 0.2513          | 0.9        | 0.9630     | 0.8        | 0.8261     | 0.9231     | 0.8824 |
| 0.1427        | 43.75 | 700  | 0.2581          | 0.9180     | 0.9756     | 0.8475     | 0.8810     | 0.8889     | 0.9022 |
| 0.1457        | 50.0  | 800  | 0.2428          | 0.8852     | 0.9512     | 0.8        | 0.8261     | 0.92       | 0.8765 |
| 0.1311        | 56.25 | 900  | 0.2462          | 0.9        | 0.9512     | 0.8        | 0.8352     | 0.9231     | 0.8819 |
| 0.1346        | 62.5  | 1000 | 0.2426          | 0.8852     | 0.9512     | 0.8421     | 0.8539     | 0.9412     | 0.8947 |


### Framework versions

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