metadata
language:
- gl
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large-V2 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: 5.701587521184242
Whisper Large-V2 Galician
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_13_0 gl dataset. It achieves the following results on the evaluation set:
- Loss: 0.2981
- Wer: 5.7016
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 |
|---|---|---|---|---|
| 0.0659 | 5.83 | 1000 | 0.1663 | 5.9593 |
| 0.0164 | 11.66 | 2000 | 0.1947 | 5.5044 |
| 0.0069 | 17.49 | 3000 | 0.2165 | 5.7500 |
| 0.0052 | 23.32 | 4000 | 0.2292 | 5.9212 |
| 0.0032 | 29.15 | 5000 | 0.2320 | 5.8884 |
| 0.0037 | 34.99 | 6000 | 0.2434 | 6.0647 |
| 0.0022 | 40.82 | 7000 | 0.2465 | 6.1114 |
| 0.0019 | 46.65 | 8000 | 0.2531 | 5.8590 |
| 0.0009 | 52.48 | 9000 | 0.2567 | 5.8451 |
| 0.001 | 58.31 | 10000 | 0.2718 | 5.7673 |
| 0.0011 | 64.14 | 11000 | 0.2659 | 6.1045 |
| 0.0008 | 69.97 | 12000 | 0.2765 | 6.0405 |
| 0.0006 | 75.8 | 13000 | 0.2793 | 6.0250 |
| 0.0004 | 81.63 | 14000 | 0.2848 | 6.0025 |
| 0.0005 | 87.46 | 15000 | 0.2790 | 5.9454 |
| 0.0002 | 93.29 | 16000 | 0.2884 | 5.8175 |
| 0.0002 | 99.13 | 17000 | 0.2913 | 5.7898 |
| 0.0001 | 104.96 | 18000 | 0.2901 | 5.7258 |
| 0.0001 | 110.79 | 19000 | 0.2991 | 5.7050 |
| 0.0001 | 116.62 | 20000 | 0.2981 | 5.7016 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1