metadata
library_name: transformers
language:
- eu
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Large-V3 Basque
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_17_0 eu
type: mozilla-foundation/common_voice_17_0
config: eu
split: test
args: eu
metrics:
- name: Wer
type: wer
value: 6.386272857195206
Whisper Large-V3 Basque
This model is a fine-tuned version of openai/whisper-large-v3 on the mozilla-foundation/common_voice_17_0 eu dataset. It achieves the following results on the evaluation set:
- Loss: 0.2570
- Wer: 6.3863
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: 3.75e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 40000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0674 | 2.3474 | 1000 | 0.1613 | 9.7732 |
| 0.0299 | 4.6948 | 2000 | 0.1633 | 8.9771 |
| 0.0164 | 7.0423 | 3000 | 0.1828 | 8.6381 |
| 0.0098 | 9.3897 | 4000 | 0.1870 | 8.2524 |
| 0.0105 | 11.7371 | 5000 | 0.1912 | 8.4146 |
| 0.0085 | 14.0845 | 6000 | 0.2029 | 8.5914 |
| 0.0076 | 16.4319 | 7000 | 0.2084 | 8.1296 |
| 0.0059 | 18.7793 | 8000 | 0.2028 | 8.1003 |
| 0.0059 | 21.1268 | 9000 | 0.2066 | 8.3404 |
| 0.0049 | 23.4742 | 10000 | 0.2154 | 8.3972 |
| 0.0044 | 25.8216 | 11000 | 0.2136 | 8.0087 |
| 0.0012 | 28.1690 | 12000 | 0.2111 | 7.3116 |
| 0.0038 | 30.5164 | 13000 | 0.2219 | 8.1471 |
| 0.0025 | 32.8638 | 14000 | 0.2155 | 7.6679 |
| 0.0021 | 35.2113 | 15000 | 0.2239 | 7.4893 |
| 0.0021 | 37.5587 | 16000 | 0.2277 | 7.8337 |
| 0.0017 | 39.9061 | 17000 | 0.2254 | 7.8108 |
| 0.0012 | 42.2535 | 18000 | 0.2247 | 7.2914 |
| 0.0021 | 44.6009 | 19000 | 0.2301 | 8.0005 |
| 0.0016 | 46.9484 | 20000 | 0.2346 | 7.7568 |
| 0.001 | 49.2958 | 21000 | 0.2283 | 7.3940 |
| 0.0021 | 51.6432 | 22000 | 0.2297 | 7.5589 |
| 0.0013 | 53.9906 | 23000 | 0.2324 | 7.6029 |
| 0.0004 | 56.3380 | 24000 | 0.2333 | 6.9369 |
| 0.0003 | 58.6854 | 25000 | 0.2254 | 6.8114 |
| 0.0016 | 61.0329 | 26000 | 0.2393 | 7.6688 |
| 0.0001 | 63.3803 | 27000 | 0.2279 | 6.8819 |
| 0.0 | 65.7277 | 28000 | 0.2320 | 6.8269 |
| 0.0 | 68.0751 | 29000 | 0.2421 | 6.5832 |
| 0.0 | 70.4225 | 30000 | 0.2481 | 6.4770 |
| 0.0 | 72.7700 | 31000 | 0.2532 | 6.4000 |
| 0.0 | 75.1174 | 32000 | 0.2570 | 6.3863 |
| 0.0011 | 77.4648 | 33000 | 0.2388 | 7.2392 |
| 0.0 | 79.8122 | 34000 | 0.2403 | 6.8223 |
| 0.0 | 82.1596 | 35000 | 0.2477 | 6.6639 |
| 0.0 | 84.5070 | 36000 | 0.2528 | 6.6071 |
| 0.0001 | 86.8545 | 37000 | 0.2562 | 6.5503 |
| 0.0 | 89.2019 | 38000 | 0.2597 | 6.4971 |
| 0.0 | 91.5493 | 39000 | 0.2623 | 6.4632 |
| 0.0 | 93.8967 | 40000 | 0.2636 | 6.4568 |
Framework versions
- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1