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---
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