metadata
language:
- gl
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large-V3 Galician
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 gl
type: mozilla-foundation/common_voice_13_0
config: gl
split: validation
args: gl
metrics:
- name: Wer
type: wer
value: 5.309030539895549
Whisper Large-V3 Galician
This model is a fine-tuned version of openai/whisper-large-v3 on the mozilla-foundation/common_voice_13_0 gl dataset. It achieves the following results on the evaluation set:
- Loss: 0.2735
- Wer: 5.3090
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0761 | 5.83 | 1000 | 0.1531 | 6.0959 |
| 0.0148 | 11.66 | 2000 | 0.1874 | 5.7327 |
| 0.0076 | 17.49 | 3000 | 0.2062 | 5.7587 |
| 0.0035 | 23.32 | 4000 | 0.2196 | 5.4491 |
| 0.0029 | 29.15 | 5000 | 0.2265 | 5.5892 |
| 0.0027 | 34.99 | 6000 | 0.2376 | 5.8365 |
| 0.0028 | 40.82 | 7000 | 0.2396 | 5.6964 |
| 0.0021 | 46.65 | 8000 | 0.2449 | 5.4820 |
| 0.0012 | 52.48 | 9000 | 0.2438 | 5.4491 |
| 0.0014 | 58.31 | 10000 | 0.2490 | 5.5581 |
| 0.0009 | 64.14 | 11000 | 0.2462 | 5.3696 |
| 0.0006 | 69.97 | 12000 | 0.2598 | 5.6307 |
| 0.0008 | 75.8 | 13000 | 0.2543 | 5.6013 |
| 0.0003 | 81.63 | 14000 | 0.2582 | 5.3609 |
| 0.0003 | 87.46 | 15000 | 0.2591 | 5.3402 |
| 0.0003 | 93.29 | 16000 | 0.2657 | 5.3609 |
| 0.0002 | 99.13 | 17000 | 0.2661 | 5.3869 |
| 0.0001 | 104.96 | 18000 | 0.2704 | 5.3177 |
| 0.0001 | 110.79 | 19000 | 0.2750 | 5.3159 |
| 0.0001 | 116.62 | 20000 | 0.2735 | 5.3090 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1