whisper-large-es – AI Model by javilonso | AlphaNeural AI

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javilonso/
whisper-large-es

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automatic-speech-recognition

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mozilla-foundation/common_voice_11_0

endpoints_compatible

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Whisper Large Es - Javier Alonso

This model is a fine-tuned version of openai/whisper-large on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.1571
Wer: 5.5201

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: 8
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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
0.211	0.1	1000	0.2293	8.3896
0.2227	0.2	2000	0.2215	8.2552
0.1496	0.3	3000	0.2121	8.0362
0.1851	0.4	4000	0.2018	7.5197
0.1917	0.5	5000	0.1916	7.1098
0.1857	0.6	6000	0.1817	6.5537
0.1294	0.7	7000	0.1752	6.4062
0.1358	0.8	8000	0.1670	5.9950
0.1542	0.9	9000	0.1604	5.7858
0.1554	1.0	10000	0.1571	5.5201

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.10.0+cu111
Datasets 2.8.1.dev0
Tokenizers 0.13.2