| --- |
| language: |
| - en |
| license: apache-2.0 |
| base_model: openai/whisper-large-v3 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: FULL6 |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # FULL6 |
|
|
| This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the FULL-2024-11-22 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3933 |
| - Wer Ortho: 21.7759 |
| - Wer: 15.7318 |
|
|
| ## 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: 300 |
| - training_steps: 2000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| |
| | 0.688 | 0.3661 | 200 | 0.4873 | 26.5992 | 19.7836 | |
| | 0.5254 | 0.7323 | 400 | 0.4390 | 24.6602 | 18.1855 | |
| | 0.4648 | 1.0984 | 600 | 0.4158 | 22.9719 | 16.9557 | |
| | 0.4014 | 1.4645 | 800 | 0.4072 | 23.2981 | 17.1182 | |
| | 0.3921 | 1.8307 | 1000 | 0.3984 | 22.3407 | 16.2132 | |
| | 0.3684 | 2.1968 | 1200 | 0.3965 | 22.2350 | 16.3119 | |
| | 0.3326 | 2.5629 | 1400 | 0.3936 | 21.8665 | 15.6564 | |
| | 0.3331 | 2.9291 | 1600 | 0.3921 | 21.5282 | 15.4852 | |
| | 0.3032 | 3.2952 | 1800 | 0.3921 | 21.9390 | 15.8565 | |
| | 0.3007 | 3.6613 | 2000 | 0.3933 | 21.7759 | 15.7318 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.44.0 |
| - Pytorch 1.13.1+cu117 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
| |
