xezpeleta/whisper-small-eu

Whisper Small Basque

This model is a fine-tuned version of openai/whisper-small on the asierhv/composite_corpus_eu_v2.1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.2353
• Wer: 9.5479

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: 1.25e-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: 10000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.3863	0.1	1000	0.4090	21.2189
0.1897	0.2	2000	0.3457	15.4490
0.1379	0.3	3000	0.3283	13.5756
0.1825	0.4	4000	0.3024	12.3954
0.0775	0.5	5000	0.3198	11.8771
0.0975	0.6	6000	0.2924	11.2589
0.1132	0.7	7000	0.2969	10.8468
0.0852	0.8	8000	0.2237	9.7727
0.0585	0.9	9000	0.2317	9.6291
0.0654	1.0	10000	0.2353	9.5479

Framework versions

• Transformers 4.49.0.dev0
• Pytorch 2.6.0+cu124
• Datasets 3.3.1.dev0
• Tokenizers 0.21.0