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# metric_classifier

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 440  | 0.0052          | 1.0      |
| 0.3727        | 2.0   | 880  | 0.0014          | 1.0      |
| 0.0028        | 3.0   | 1320 | 0.0007          | 1.0      |
| 0.0011        | 4.0   | 1760 | 0.0004          | 1.0      |
| 0.0006        | 5.0   | 2200 | 0.0003          | 1.0      |
| 0.0004        | 6.0   | 2640 | 0.0002          | 1.0      |
| 0.0003        | 7.0   | 3080 | 0.0002          | 1.0      |
| 0.0002        | 8.0   | 3520 | 0.0001          | 1.0      |
| 0.0002        | 9.0   | 3960 | 0.0001          | 1.0      |
| 0.0002        | 10.0  | 4400 | 0.0001          | 1.0      |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "metric_classifier", "results": []}]}
transformers tensorboard safetensors distilbert text-classification generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us