|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: facebook/w2v-bert-2.0 |
|
|
tags: |
|
|
- automatic-speech-recognition |
|
|
- CLEAR-Global/luo_19h |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- wer |
|
|
model-index: |
|
|
- name: w2v-bert-2.0-luo_cv_fleurs_19h-v4 |
|
|
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. --> |
|
|
|
|
|
# w2v-bert-2.0-luo_cv_fleurs_19h-v4 |
|
|
|
|
|
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the CLEAR-GLOBAL/LUO_19H - NA dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.2866 |
|
|
- Wer: 0.3289 |
|
|
- Cer: 0.0998 |
|
|
|
|
|
## 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: 1e-05 |
|
|
- train_batch_size: 32 |
|
|
- eval_batch_size: 32 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 2 |
|
|
- total_train_batch_size: 64 |
|
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_ratio: 0.025 |
|
|
- training_steps: 100000 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
|
|
| 0.5991 | 6.4935 | 1000 | 0.6712 | 0.5595 | 0.1797 | |
|
|
| 0.231 | 12.9870 | 2000 | 0.3213 | 0.3638 | 0.1045 | |
|
|
| 0.1231 | 19.4805 | 3000 | 0.2866 | 0.3285 | 0.0990 | |
|
|
| 0.0514 | 25.9740 | 4000 | 0.2907 | 0.3122 | 0.0961 | |
|
|
| 0.0294 | 32.4675 | 5000 | 0.3262 | 0.3073 | 0.0932 | |
|
|
| 0.0264 | 38.9610 | 6000 | 0.3543 | 0.3047 | 0.0945 | |
|
|
| 0.0116 | 45.4545 | 7000 | 0.3592 | 0.3104 | 0.0963 | |
|
|
| 0.009 | 51.9481 | 8000 | 0.3849 | 0.3355 | 0.0949 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.48.1 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.5.0 |
|
|
- Tokenizers 0.21.1 |
|
|
|
