whisper-small-sv-extra-data
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_13_0 and the google/fleurs datasets. It achieves the following results on the evaluation set:
- Loss: 0.3843
- Wer: 22.1585
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.3189 | 0.53 | 500 | 0.3610 | 25.2029 |
0.1451 | 1.05 | 1000 | 0.3337 | 23.6495 |
0.1432 | 1.58 | 1500 | 0.3263 | 22.8908 |
0.0572 | 2.1 | 2000 | 0.3284 | 22.1622 |
0.0502 | 2.63 | 2500 | 0.3405 | 22.2000 |
0.0259 | 3.15 | 3000 | 0.3596 | 22.1924 |
0.0246 | 3.68 | 3500 | 0.3650 | 22.2208 |
0.0137 | 4.2 | 4000 | 0.3843 | 22.1585 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for Sleepyp00/whisper-small-sv-extra-data
Base model
openai/whisper-smallDatasets used to train Sleepyp00/whisper-small-sv-extra-data
Evaluation results
- Wer on mozilla-foundation/common_voice_13_0test set self-reported22.158
- Wer on google/fleursself-reported22.158