
# distilbert-base-uncased-finetuned-imdb-whole-word-masking

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [IMDB](https://huggingface.co/datasets/imdb) dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0554

## Model description

The model is trained using whole word masking.

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2819        | 1.0   | 782  | 3.1161          |
| 3.2058        | 2.0   | 1564 | 3.0585          |
| 3.1674        | 3.0   | 2346 | 3.0554          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased-finetuned-imdb-whole-word-masking", "results": []}]}
transformers tensorboard safetensors distilbert fill-mask generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us