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# bert_finetuned

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: 0.3964
- Accuracy: 0.8372
- Roc Auc: 0.8947

## 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: 1e-05
- train_batch_size: 256
- eval_batch_size: 256
- 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 | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|
| No log        | 1.0   | 24   | 0.5231          | 0.7951   | 0.8627  |
| No log        | 2.0   | 48   | 0.4093          | 0.8332   | 0.8930  |
| No log        | 3.0   | 72   | 0.3950          | 0.8418   | 0.8965  |
| No log        | 4.0   | 96   | 0.3890          | 0.8398   | 0.8976  |
| No log        | 5.0   | 120  | 0.3931          | 0.8359   | 0.8962  |
| No log        | 6.0   | 144  | 0.4052          | 0.8273   | 0.8957  |
| No log        | 7.0   | 168  | 0.3935          | 0.8372   | 0.8958  |
| No log        | 8.0   | 192  | 0.3998          | 0.8319   | 0.8953  |
| No log        | 9.0   | 216  | 0.3934          | 0.8385   | 0.8949  |
| No log        | 10.0  | 240  | 0.3964          | 0.8372   | 0.8947  |


### Framework versions

- Transformers 4.37.1
- Pytorch 1.13.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.1

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