---
license: mit
base_model: distil-whisper/distil-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: rao-vandromme-purcell-distil-finetuned
  results: []
---

<!-- 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. -->

# rao-vandromme-purcell-distil-finetuned

This model is a fine-tuned version of [distil-whisper/distil-large-v2](https://huggingface.co/distil-whisper/distil-large-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0590
- Wer: 2.9688

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6205        | 0.29  | 10   | 0.2496          | 3.4375 |
| 0.073         | 0.59  | 20   | 0.0745          | 2.5    |
| 0.2899        | 0.88  | 30   | 0.0647          | 3.125  |
| 0.034         | 1.18  | 40   | 0.0674          | 3.2812 |
| 0.0507        | 1.47  | 50   | 0.0590          | 2.9688 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0