metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./300
results: []
./300
This model is a fine-tuned version of openai/whisper-medium.en on the 300 SF 1000 dataset. It achieves the following results on the evaluation set:
- Loss: 0.75
- Wer Ortho: 33.0175
- Wer: 21.3491
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- 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: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.6187 | 5.2632 | 100 | 1.1230 | 41.5087 | 30.1041 |
| 0.7964 | 10.5263 | 200 | 0.8076 | 31.8878 | 20.2368 |
| 0.5424 | 15.7895 | 300 | 0.7627 | 31.7055 | 20.0933 |
| 0.4204 | 21.0526 | 400 | 0.7495 | 33.1268 | 21.2056 |
| 0.3666 | 26.3158 | 500 | 0.75 | 33.0175 | 21.3491 |
Framework versions
- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1