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

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# binary_classification

- Loss: 0.0159
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0

## 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: 64
- eval_batch_size: 64
- 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   | 9    | 0.0159          | 1.0       | 1.0    | 1.0 | 1.0      |
| No log        | 2.0   | 18   | 0.0030          | 1.0       | 1.0    | 1.0 | 1.0      |
| No log        | 3.0   | 27   | 0.0023          | 1.0       | 1.0    | 1.0 | 1.0      |
| No log        | 4.0   | 36   | 0.0028          | 1.0       | 1.0    | 1.0 | 1.0      |
| No log        | 5.0   | 45   | 0.0018          | 1.0       | 1.0    | 1.0 | 1.0      |
| No log        | 6.0   | 54   | 0.0011          | 1.0       | 1.0    | 1.0 | 1.0      |
| No log        | 7.0   | 63   | 0.0010          | 1.0       | 1.0    | 1.0 | 1.0      |
| No log        | 8.0   | 72   | 0.0010          | 1.0       | 1.0    | 1.0 | 1.0      |


### Framework versions

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