---
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: logs
  results: []
---

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

- Loss: 0.0008
- Precision: 0.9900
- Recall: 0.995
- F1: 0.9925
- Accuracy: 0.9999

## 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: 16
- eval_batch_size: 16
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 44   | 0.0039          | 0.9701    | 0.975  | 0.9726 | 0.9991   |
| No log        | 2.0   | 88   | 0.0018          | 0.8744    | 0.94   | 0.9060 | 0.9995   |
| No log        | 3.0   | 132  | 0.0011          | 0.9559    | 0.975  | 0.9653 | 0.9998   |
| No log        | 4.0   | 176  | 0.0008          | 0.9900    | 0.995  | 0.9925 | 0.9999   |
| No log        | 5.0   | 220  | 0.0007          | 0.9803    | 0.995  | 0.9876 | 0.9999   |
| No log        | 6.0   | 264  | 0.0007          | 0.9851    | 0.995  | 0.9900 | 0.9999   |
| No log        | 7.0   | 308  | 0.0007          | 0.9900    | 0.995  | 0.9925 | 0.9999   |
| No log        | 8.0   | 352  | 0.0007          | 0.9803    | 0.995  | 0.9876 | 0.9999   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.0.1
- Datasets 2.19.1
- Tokenizers 0.19.1