test
This model is a fine-tuned version of openai/whisper-base on the whisper_fleurs_ver1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5203
- Cer: 10.9470
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: 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.0347 | 6.29 | 1000 | 0.4469 | 10.9426 |
| 0.0046 | 12.58 | 2000 | 0.4908 | 10.8907 |
| 0.0025 | 18.87 | 3000 | 0.5122 | 10.9946 |
| 0.0019 | 25.16 | 4000 | 0.5203 | 10.9470 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for unanam/fleurstest
Base model
openai/whisper-base