whisper-largev2-mls-es

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Whisper largeV2 Spanish MLS

This model is a fine-tuned version of openai/whisper-large-v2 on the facebook/multilingual_librispeech spanish dataset. It achieves the following results on the evaluation set:

• Loss: 0.0910
• Wer: 3.4678

Model description

The model is fine-tuned for 4000 updates/steps on multilingual librispeech Spanish train data.

• Zero-shot - 4.2 (MLS Spanish test)
• Fine-tune MLS spanish train - 3.46 (MLS Spanish test) (-17.61%)

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• Zero-shot - 6.3 (CV11 test)
• Fine-tune MLS spanish train - 8.38 (CV11 test)

When the model is fine-tuned on specific dataset, the model loose its ability to generalise across datasets. Here the model is fine-tuned on MLS Spanish and evaluated on CV11 Spanish test. We can observe the drop in performance on CV11 test data.

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: 8
• 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: 4000
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0+cu117
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2