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# hface_mlops_demo_dbert

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: 0.4284
- Accuracy: 0.8

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 5    | 0.6335          | 0.675    |
| 0.6036        | 2.0   | 10   | 0.5269          | 0.725    |
| 0.6036        | 3.0   | 15   | 0.4589          | 0.775    |
| 0.3639        | 4.0   | 20   | 0.4284          | 0.8      |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
{"license": "apache-2.0", "tags": ["generated_from_trainer", "njay"], "metrics": ["accuracy"], "author": "njay", "base_model": "distilbert-base-uncased", "model-index": [{"name": "hface_mlops_demo_dbert", "results": []}]}
transformers pytorch distilbert text-classification generated_from_trainer njay base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us