metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./openai/whisper-large-v3-cit-do015-wd0-lr3e-06-FULL
results: []
./openai/whisper-large-v3-cit-do015-wd0-lr3e-06-FULL
This model is a fine-tuned version of openai/whisper-large-v3 on the FULL dataset. It achieves the following results on the evaluation set:
- Loss: 0.5117
- Wer Ortho: 27.7362
- Wer: 18.6050
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: 3e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- 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: 100
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.9582 | 0.4773 | 50 | 0.6479 | 34.9922 | 25.6303 |
| 0.6764 | 0.9547 | 100 | 0.5605 | 30.9901 | 21.5126 |
| 0.5263 | 1.4320 | 150 | 0.5337 | 29.3892 | 20.0168 |
| 0.5084 | 1.9093 | 200 | 0.5186 | 28.0842 | 19.1261 |
| 0.4226 | 2.3866 | 250 | 0.5132 | 27.9624 | 18.8571 |
| 0.4078 | 2.8640 | 300 | 0.5083 | 28.1538 | 19.0420 |
| 0.3775 | 3.3413 | 350 | 0.5083 | 28.3974 | 18.8403 |
| 0.3532 | 3.8186 | 400 | 0.5093 | 28.1538 | 18.6555 |
| 0.3359 | 4.2959 | 450 | 0.5098 | 27.7188 | 18.5210 |
| 0.3189 | 4.7733 | 500 | 0.5117 | 27.7362 | 18.6050 |
Framework versions
- Transformers 4.42.4
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1