metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./1000
results: []
./1000
This model is a fine-tuned version of openai/whisper-medium.en on the 1000 SF 1000 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6318
- Wer Ortho: 32.5802
- Wer: 21.4926
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: 5e-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: 800
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.1316 | 1.7699 | 100 | 0.6968 | 29.0816 | 18.8733 |
| 0.4669 | 3.5398 | 200 | 0.5156 | 27.4417 | 17.5816 |
| 0.2075 | 5.3097 | 300 | 0.5303 | 27.6968 | 16.7205 |
| 0.1163 | 7.0796 | 400 | 0.5391 | 28.6443 | 17.8687 |
| 0.0712 | 8.8496 | 500 | 0.5811 | 28.9723 | 17.5816 |
| 0.0518 | 10.6195 | 600 | 0.6104 | 31.8513 | 21.2415 |
| 0.0388 | 12.3894 | 700 | 0.6245 | 32.4344 | 21.4926 |
| 0.034 | 14.1593 | 800 | 0.6318 | 32.5802 | 21.4926 |
Framework versions
- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1