whisper-large-v2-french-2
This model is a fine-tuned version of openai/whisper-large-v2 on the COMMON_VOICE_13_0 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2931
- eval_wer_ortho: 0.1809
- eval_wer: 0.1322
- eval_runtime: 19643.029
- eval_samples_per_second: 0.82
- eval_steps_per_second: 0.41
- epoch: 2.0
- step: 4190
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
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Base model
openai/whisper-large-v2