zuazo/whisper-large-v2-es

Whisper Large-V2 Spanish

This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_13_0 es dataset. It achieves the following results on the evaluation set:

• Loss: 0.2544
• Wer: 4.8949

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: 1e-05
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 20000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0869	2.0	1000	0.1754	6.1516
0.0913	4.0	2000	0.1652	5.7500
0.051	6.0	3000	0.1643	5.7757
0.0391	8.0	4000	0.1881	5.6589
0.0104	10.0	5000	0.2026	5.6211
0.0806	12.01	6000	0.1741	5.7398
0.0077	14.01	7000	0.2119	5.6038
0.0357	16.01	8000	0.1776	5.6147
0.1087	18.01	9000	0.1868	5.5172
0.0401	20.01	10000	0.2014	5.4428
0.0334	22.01	11000	0.1751	5.2824
0.0071	24.01	12000	0.2295	5.2490
0.0374	26.01	13000	0.2098	5.2574
0.0023	28.01	14000	0.2498	5.0418
0.0025	30.01	15000	0.2311	4.9385
0.0006	32.01	16000	0.2544	4.8949
0.0009	34.02	17000	0.2691	5.1246
0.003	36.02	18000	0.2249	5.0277
0.0009	38.02	19000	0.2603	5.0373
0.0008	40.02	20000	0.2657	5.0225

Framework versions

• Transformers 4.33.0.dev0
• Pytorch 2.0.1+cu117
• Datasets 2.14.4
• Tokenizers 0.13.3