|
--- |
|
language: |
|
- nl |
|
license: apache-2.0 |
|
base_model: openai/whisper-large-v2 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Large V2 |
|
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. --> |
|
|
|
# Whisper Large V2 |
|
|
|
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4660 |
|
- Wer: 14.5440 |
|
|
|
## 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-05 |
|
- 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: 20 |
|
- num_epochs: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.7649 | 0.55 | 30 | 0.4569 | 21.4116 | |
|
| 0.3718 | 1.09 | 60 | 0.4107 | 14.9247 | |
|
| 0.2053 | 1.64 | 90 | 0.3970 | 17.1451 | |
|
| 0.1836 | 2.18 | 120 | 0.4242 | 14.0523 | |
|
| 0.092 | 2.73 | 150 | 0.4120 | 14.4330 | |
|
| 0.0648 | 3.27 | 180 | 0.4352 | 15.5115 | |
|
| 0.0359 | 3.82 | 210 | 0.4290 | 15.0991 | |
|
| 0.0205 | 4.36 | 240 | 0.4587 | 14.6392 | |
|
| 0.0132 | 4.91 | 270 | 0.4660 | 14.5440 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.0.dev0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.15.0 |
|
|
