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# training

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8713
- Accuracy: 0.5183
- F1: 0.5192
- Precision: 0.5219
- Recall: 0.5183

## 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: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 66   | 0.7083          | 0.4970   | 0.4093 | 0.5891    | 0.4970 |
| No log        | 2.0   | 132  | 0.7447          | 0.4939   | 0.4486 | 0.5338    | 0.4939 |
| No log        | 3.0   | 198  | 0.7978          | 0.5      | 0.4814 | 0.5239    | 0.5    |
| No log        | 4.0   | 264  | 0.8450          | 0.5091   | 0.5100 | 0.5136    | 0.5091 |
| No log        | 5.0   | 330  | 0.8713          | 0.5183   | 0.5192 | 0.5219    | 0.5183 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "training", "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