Whisper Medium FLEURS Language Identification
This model is a fine-tuned version of openai/whisper-medium on the FLEURS subset of the google/xtreme_s dataset. It achieves the following results on the evaluation set:
- Loss: 0.8413
- Accuracy: 0.8805
To reproduce this run, execute the command in run.sh.
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 0
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0152 | 1.0 | 8494 | 0.9087 | 0.8431 |
| 0.0003 | 2.0 | 16988 | 1.0059 | 0.8460 |
| 0.0 | 3.0 | 25482 | 0.8413 | 0.8805 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.2
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