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# llm_NLP

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: 0.7458
- Matthews Correlation: 0.4922

## 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: 8.53919308272751e-06
- train_batch_size: 8
- eval_batch_size: 16
- seed: 13
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.5143        | 1.0   | 1069 | 0.4927          | 0.4359               |
| 0.3963        | 2.0   | 2138 | 0.4984          | 0.4814               |
| 0.3216        | 3.0   | 3207 | 0.6548          | 0.4980               |
| 0.2629        | 4.0   | 4276 | 0.7458          | 0.4922               |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["matthews_correlation"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "llm_NLP", "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