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---
base_model: openai/whisper-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: 12.985346941102685
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: 0.3644
- Wer: 12.9853
## 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: 8
- 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: 50
- num_epochs: 3.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.9139 | 0.1270 | 500 | 0.6388 | 24.1376 |
| 0.5572 | 0.2541 | 1000 | 0.4884 | 17.9087 |
| 0.5416 | 0.3811 | 1500 | 0.4371 | 15.2460 |
| 0.5542 | 0.5081 | 2000 | 0.4156 | 13.7921 |
| 0.6599 | 0.6352 | 2500 | 0.4036 | 13.4956 |
| 0.6117 | 0.7622 | 3000 | 0.3960 | 13.2676 |
| 0.5569 | 0.8892 | 3500 | 0.3890 | 13.1336 |
| 0.537 | 1.0163 | 4000 | 0.3850 | 12.5292 |
| 0.4677 | 1.1433 | 4500 | 0.3815 | 12.6261 |
| 0.5017 | 1.2703 | 5000 | 0.3792 | 12.4836 |
| 0.5346 | 1.3974 | 5500 | 0.3761 | 12.3126 |
| 0.4858 | 1.5244 | 6000 | 0.3735 | 12.2926 |
| 0.5478 | 1.6514 | 6500 | 0.3715 | 12.4009 |
| 0.5277 | 1.7785 | 7000 | 0.3699 | 12.2327 |
| 0.5153 | 1.9055 | 7500 | 0.3693 | 12.1643 |
| 0.5825 | 2.0325 | 8000 | 0.3681 | 12.1387 |
| 0.6049 | 2.1596 | 8500 | 0.3670 | 12.3211 |
| 0.5248 | 2.2866 | 9000 | 0.3662 | 12.1501 |
| 0.554 | 2.4136 | 9500 | 0.3653 | 12.0645 |
| 0.5031 | 2.5407 | 10000 | 0.3654 | 12.9312 |
| 0.5253 | 2.6677 | 10500 | 0.3647 | 12.9739 |
| 0.5132 | 2.7947 | 11000 | 0.3641 | 12.9511 |
| 0.5789 | 2.9217 | 11500 | 0.3644 | 12.9853 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1 |