|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-large-xlsr-53 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-xlsr-53-ft-btb-ccv-cy |
|
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. --> |
|
|
|
# wav2vec2-xlsr-53-ft-btb-ccv-cy |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6832 |
|
- Wer: 0.4641 |
|
|
|
## 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: 0.0003 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 64 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 1000 |
|
- training_steps: 10000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:-----:|:---------------:|:------:| |
|
| 4.8422 | 0.0854 | 500 | 2.2692 | 0.9886 | |
|
| 1.2704 | 0.1709 | 1000 | 1.1623 | 0.7745 | |
|
| 1.0177 | 0.2563 | 1500 | 0.9608 | 0.6586 | |
|
| 0.9289 | 0.3417 | 2000 | 0.8117 | 0.6027 | |
|
| 0.855 | 0.4271 | 2500 | 0.7981 | 0.5627 | |
|
| 0.804 | 0.5126 | 3000 | 0.7293 | 0.5387 | |
|
| 0.7384 | 0.5980 | 3500 | 0.6784 | 0.5150 | |
|
| 0.7277 | 0.6834 | 4000 | 0.6553 | 0.4961 | |
|
| 0.7009 | 0.7688 | 4500 | 0.6262 | 0.4684 | |
|
| 0.6774 | 0.8543 | 5000 | 0.5955 | 0.4525 | |
|
| 0.6427 | 0.9397 | 5500 | 0.5997 | 0.4741 | |
|
| 0.6224 | 1.0251 | 6000 | 0.5653 | 0.4310 | |
|
| 0.5507 | 1.1105 | 6500 | 0.5521 | 0.4173 | |
|
| 0.6425 | 1.1960 | 7000 | 0.9010 | 0.5927 | |
|
| 0.7218 | 1.2814 | 7500 | 0.7136 | 0.5011 | |
|
| 0.8592 | 1.3668 | 8000 | 0.8863 | 0.6393 | |
|
| 0.8668 | 1.4522 | 8500 | 0.7689 | 0.5330 | |
|
| 0.7688 | 1.5377 | 9000 | 0.7101 | 0.4776 | |
|
| 0.688 | 1.6231 | 9500 | 0.6742 | 0.4661 | |
|
| 0.7079 | 1.7085 | 10000 | 0.6832 | 0.4641 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
