
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distill-whisper-jargon

This model is a fine-tuned version of [distil-whisper/distil-small.en](https://huggingface.co/distil-whisper/distil-small.en) on the [btemirov/fin-terms](https://huggingface.co/datasets/btemirov/fin-terms) dataset.
It achieves the following results on the evaluation set:
- Loss: 4.4314
- Wer: 78.4173

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 3.8199        | 22.22  | 100  | 3.5227          | 79.3525 |
| 2.3504        | 44.44  | 200  | 3.7073          | 77.3022 |
| 1.4612        | 66.67  | 300  | 4.1042          | 78.6691 |
| 0.9713        | 88.89  | 400  | 4.3164          | 77.7698 |
| 0.7453        | 111.11 | 500  | 4.4314          | 78.4173 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "distil-whisper/distil-small.en", "model-index": [{"name": "distill-whisper-jargon", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer base_model:distil-whisper/distil-small.en license:mit endpoints_compatible region:us