whisper-small-pt-cv16-fleurs

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whisper-small-pt-cv16-fleurs

This model is a fine-tuned version of openai/whisper-small on the fsicoli/cv16-fleurs default dataset. It achieves the following results on the evaluation set:

• Loss: 0.2154
• Wer: 0.1442

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-06
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• total_train_batch_size: 16
• total_eval_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 5000
• training_steps: 5000

Training results

Framework versions

• Transformers 4.39.0.dev0
• Pytorch 2.2.1
• Datasets 2.16.1
• Tokenizers 0.15.2