---
base_model: distil-whisper/distil-large-v3
datasets:
- Gabi00/english-mistakes
language:
- eng
library_name: peft
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper Small Eng - Gabriel Mora
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: English-mistakes
      type: Gabi00/english-mistakes
      config: default
      split: validation
      args: 'config: eng, split: test'
    metrics:
    - type: wer
      value: 18.233650721249788
      name: Wer
---

<!-- 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. -->

# Whisper Small Eng - Gabriel Mora

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the English-mistakes dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6550
- Wer: 18.2337

## 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: 28
- eval_batch_size: 28
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 100000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 1.5085        | 0.4444 | 500   | 1.1844          | 25.9507 |
| 1.1717        | 0.8889 | 1000  | 0.9522          | 25.2751 |
| 1.1302        | 1.3333 | 1500  | 0.8634          | 22.0879 |
| 1.0094        | 1.7778 | 2000  | 0.8098          | 21.0103 |
| 1.0509        | 2.2222 | 2500  | 0.7784          | 23.2054 |
| 0.9722        | 2.6667 | 3000  | 0.7555          | 21.5206 |
| 0.9562        | 3.1111 | 3500  | 0.7401          | 21.0075 |
| 0.9995        | 3.5556 | 4000  | 0.7269          | 19.8985 |
| 0.9497        | 4.0    | 4500  | 0.7170          | 19.3626 |
| 0.8703        | 4.4444 | 5000  | 0.7078          | 19.4652 |
| 1.0015        | 4.8889 | 5500  | 0.7004          | 20.1608 |
| 0.9248        | 5.3333 | 6000  | 0.6947          | 17.7034 |
| 0.9163        | 5.7778 | 6500  | 0.6880          | 17.4953 |
| 0.8833        | 6.2222 | 7000  | 0.6823          | 17.4668 |
| 0.9051        | 6.6667 | 7500  | 0.6770          | 17.4554 |
| 0.8882        | 7.1111 | 8000  | 0.6730          | 17.3613 |
| 0.8879        | 7.5556 | 8500  | 0.6684          | 18.3220 |
| 0.8396        | 8.0    | 9000  | 0.6647          | 18.2165 |
| 0.9282        | 8.4444 | 9500  | 0.6616          | 18.4646 |
| 0.8581        | 8.8889 | 10000 | 0.6578          | 18.1538 |
| 0.8938        | 9.3333 | 10500 | 0.6550          | 18.2337 |


### Framework versions

- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1