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---
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 |