Whisper Medium Mixed-Italian
This model is a fine-tuned version of openai/whisper-medium on the it datasets:
- mozilla-foundation/common_voice_17_0
- google/fleurs
- facebook/multilingual_librispeech
- facebook/voxpopuli
It achieves the following results on the evaluation set:
- Loss: 0.1318
- Wer: 6.8401
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: 32
- 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: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1502 | 0.2 | 1000 | 0.1708 | 9.0922 |
0.1584 | 0.4 | 2000 | 0.1554 | 8.1757 |
0.1309 | 0.6 | 3000 | 0.1426 | 7.4142 |
0.0984 | 0.8 | 4000 | 0.1370 | 7.1298 |
0.0933 | 1.0 | 5000 | 0.1318 | 6.8401 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
openai/whisper-mediumDatasets used to train deepdml/whisper-medium-mix-it
Evaluation results
- Wer on mozilla-foundation/common_voice_17_0 ittest set self-reported6.840
- WER on google/fleurstest set self-reported3.750
- WER on facebook/multilingual_librispeechtest set self-reported11.440
- WER on facebook/voxpopulitest set self-reported17.940