metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v2-3swissdatasets
results: []
whisper-large-v2-3swissdatasets
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2418
- Wer: 16.0707
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 7000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2962 | 0.0727 | 1000 | 0.3163 | 20.0659 |
| 0.2756 | 0.1454 | 2000 | 0.2962 | 19.2670 |
| 0.2405 | 0.2181 | 3000 | 0.2771 | 18.1353 |
| 0.2917 | 0.2908 | 4000 | 0.2644 | 17.5769 |
| 0.2117 | 0.3635 | 5000 | 0.2536 | 16.7275 |
| 0.2334 | 0.4362 | 6000 | 0.2455 | 16.3825 |
| 0.2408 | 0.5089 | 7000 | 0.2418 | 16.0707 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.3.1+cu118
- Datasets 3.2.0
- Tokenizers 0.19.1