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# distilbert-base-uncased-finetuned-source-recognition

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: 0.1588
- Accuracy: 0.9550
- Precision: 0.9550
- Recall: 0.9550
- F1: 0.9550

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.132         | 1.0   | 3009  | 0.1251          | 0.9568   | 0.9568    | 0.9568 | 0.9568 |
| 0.1066        | 2.0   | 6018  | 0.1184          | 0.9591   | 0.9592    | 0.9591 | 0.9591 |
| 0.078         | 3.0   | 9027  | 0.1432          | 0.9598   | 0.9598    | 0.9598 | 0.9598 |
| 0.0527        | 4.0   | 12036 | 0.1773          | 0.9589   | 0.9591    | 0.9589 | 0.9589 |
| 0.0313        | 5.0   | 15045 | 0.2088          | 0.9591   | 0.9591    | 0.9591 | 0.9591 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

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