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whisper-base-es – AI Model by CheeLi03 | AlphaNeural AI
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whisper-base-es
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tensorboard
safetensors
whisper
hf-asr-leaderboard
generated_from_trainer
es
fleurs
openai/whisper-base
finetune
apache-2.0
model-index
us
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Whisper Base Spanish - Chee Li
This model is a fine-tuned version of
openai/whisper-base
on the Google Fleurs dataset. It achieves the following results on the evaluation set:
Loss: 0.3590
Wer: 22.0101
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: 16
eval_batch_size: 8
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: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.5048
4.9751
1000
0.2942
16.3314
0.2077
9.9502
2000
0.3299
17.1524
0.0999
14.9254
3000
0.3504
19.7189
0.0614
19.9005
4000
0.3590
22.0101
Framework versions
Transformers 4.43.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
