metadata
language:
- ca
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Catalan
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 ca
type: mozilla-foundation/common_voice_13_0
config: ca
split: test
args: ca
metrics:
- name: Wer
type: wer
value: 10.025150042869392
Whisper Small Catalan
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_13_0 ca dataset. It achieves the following results on the evaluation set:
- Loss: 0.2169
- Wer: 10.0252
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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1708 | 1.1 | 1000 | 0.2494 | 12.1846 |
| 0.0421 | 3.09 | 2000 | 0.2458 | 11.2689 |
| 0.0761 | 5.09 | 3000 | 0.2340 | 10.9231 |
| 0.0928 | 7.08 | 4000 | 0.2150 | 10.0394 |
| 0.0504 | 9.08 | 5000 | 0.2169 | 10.0252 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3