whisper-large-v3-turbo-FLEURS-GL

This model is a fine-tuned version of openai/whisper-large-v3-turbo on juanjucm/FLEURS-SpeechT-GL-EN. It achieves the following results on the evaluation set:

• Loss: 0.2522
• Wer: 9.1731

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-06
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• total_train_batch_size: 32
• total_eval_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.125	1.0	86	0.2128	10.1464
0.0835	2.0	172	0.2006	9.4315
0.0322	3.0	258	0.2091	9.6985
0.0115	4.0	344	0.2325	9.8880
0.0127	5.0	430	0.2313	9.2506
0.0022	7.0	602	0.2498	9.2679
0.0021	6.0	516	0.2412	9.3885
0.0011	8.0	688	0.2522	9.1731
0.0017	9.0	774	0.2538	9.3023
0.0011	10.0	860	0.2556	9.2937

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.20.0