---
tags:
- generated_from_trainer
metrics:
- recall
- precision
- f1
model-index:
- name: checkpoint-291-3ep3bsfrmulti4
  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. -->

# checkpoint-291-3ep3bsfrmulti4

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2616
- Recall: 0.9032
- Precision: 0.9655
- F1: 0.9333
- Roc Auc: 0.8333

## 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: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 291

### Training results

| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:-------:|
| 0.0           | 0.33  | 97   | 0.1037          | 0.9677 | 1.0       | 0.9836 | 0.4248  |
| 0.0001        | 1.33  | 194  | 0.8674          | 1.0    | 0.62      | 0.7654 | 0.1087  |
| 0.0001        | 2.33  | 291  | 0.2616          | 0.9032 | 0.9655    | 0.9333 | 0.8333  |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.2