metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- asierhv/composite_corpus_eu_v2.1
metrics:
- wer
model-index:
- name: Whisper Base Basque
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: asierhv/composite_corpus_eu_v2.1
type: asierhv/composite_corpus_eu_v2.1
metrics:
- name: Wer
type: wer
value: 13.816958025614658
Whisper Base Basque
This model is a fine-tuned version of openai/whisper-base on the asierhv/composite_corpus_eu_v2.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2452
- Wer: 13.8170
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- 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: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4951 | 0.125 | 1000 | 0.4901 | 27.0543 |
| 0.2607 | 0.25 | 2000 | 0.3708 | 19.8654 |
| 0.1887 | 0.375 | 3000 | 0.3454 | 18.3977 |
| 0.2607 | 0.5 | 4000 | 0.3218 | 16.8085 |
| 0.106 | 0.625 | 5000 | 0.3289 | 15.7801 |
| 0.1376 | 0.75 | 6000 | 0.3052 | 15.0276 |
| 0.1733 | 0.875 | 7000 | 0.3004 | 13.9338 |
| 0.1228 | 1.0 | 8000 | 0.2452 | 13.8170 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.2.1.dev0
- Tokenizers 0.21.0