metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- whisper-event
- generated_from_trainer
datasets:
- asierhv/composite_corpus_eu_v2.1
language:
- eu
metrics:
- wer
model-index:
- name: Whisper Medium Basque
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: eu
split: test
args:
language: eu
metrics:
- name: Test WER
type: wer
value: 7.97
- 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: 9.98410769374591
Whisper Medium Basque
This model is a fine-tuned version of openai/whisper-medium on the asierhv/composite_corpus_eu_v2.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2191
- Wer: 9.9841
- Wer on Common Voice 17.0,
test
split: 7.97
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: 6.25e-06
- train_batch_size: 16
- eval_batch_size: 8
- 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 |
---|---|---|---|---|
0.3412 | 0.0625 | 500 | 0.4570 | 28.2182 |
0.1462 | 0.125 | 1000 | 0.3524 | 19.9402 |
0.2495 | 0.1875 | 1500 | 0.3077 | 17.5236 |
0.2617 | 0.25 | 2000 | 0.2811 | 16.5841 |
0.1646 | 0.3125 | 2500 | 0.2726 | 13.8917 |
0.0934 | 0.375 | 3000 | 0.2533 | 14.0273 |
0.1016 | 0.4375 | 3500 | 0.2331 | 12.1623 |
0.1454 | 0.5 | 4000 | 0.2299 | 11.5546 |
0.1502 | 0.5625 | 4500 | 0.2333 | 12.4007 |
0.0916 | 0.625 | 5000 | 0.2271 | 10.9657 |
0.0914 | 0.6875 | 5500 | 0.2343 | 10.5029 |
0.1093 | 0.75 | 6000 | 0.2191 | 9.9841 |
0.0948 | 0.8125 | 6500 | 0.2215 | 10.5357 |
0.0744 | 0.875 | 7000 | 0.2108 | 11.2368 |
0.1269 | 0.9375 | 7500 | 0.2158 | 10.0028 |
0.1408 | 1.0 | 8000 | 0.2141 | 10.1290 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.2.1.dev0
- Tokenizers 0.21.0