Transcriber-Medium
This model is a fine-tuned version of openai/whisper-tiny on the dataset_whisper dataset. It achieves the following results on the evaluation set:
- Loss: 2.9360
- Wer: 108.5203
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.7536 | 4.02 | 100 | 2.9360 | 108.5203 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.14.1
- Tokenizers 0.13.3
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Base model
openai/whisper-tiny