|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice |
|
model-index: |
|
- name: '' |
|
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. --> |
|
|
|
# |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2318 |
|
- Wer: 0.2866 |
|
- Cer: 0.0667 |
|
|
|
## 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: 7.5e-05 |
|
- train_batch_size: 64 |
|
- eval_batch_size: 64 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- training_steps: 8692 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 3.675 | 2.3 | 400 | 3.5052 | 1.0 | 1.0 | |
|
| 3.0446 | 4.6 | 800 | 2.2759 | 1.0052 | 0.5215 | |
|
| 1.7276 | 6.9 | 1200 | 0.7083 | 0.6697 | 0.1969 | |
|
| 1.5171 | 9.2 | 1600 | 0.5328 | 0.5733 | 0.1568 | |
|
| 1.4176 | 11.49 | 2000 | 0.4571 | 0.5161 | 0.1381 | |
|
| 1.343 | 13.79 | 2400 | 0.3910 | 0.4522 | 0.1160 | |
|
| 1.2743 | 16.09 | 2800 | 0.3534 | 0.4137 | 0.1044 | |
|
| 1.2396 | 18.39 | 3200 | 0.3278 | 0.3877 | 0.0959 | |
|
| 1.2035 | 20.69 | 3600 | 0.3109 | 0.3741 | 0.0917 | |
|
| 1.1745 | 22.99 | 4000 | 0.2972 | 0.3618 | 0.0882 | |
|
| 1.1541 | 25.29 | 4400 | 0.2836 | 0.3427 | 0.0832 | |
|
| 1.1372 | 27.59 | 4800 | 0.2759 | 0.3357 | 0.0812 | |
|
| 1.1048 | 29.89 | 5200 | 0.2669 | 0.3284 | 0.0783 | |
|
| 1.0966 | 32.18 | 5600 | 0.2678 | 0.3249 | 0.0775 | |
|
| 1.0747 | 34.48 | 6000 | 0.2547 | 0.3134 | 0.0748 | |
|
| 1.0593 | 36.78 | 6400 | 0.2491 | 0.3077 | 0.0728 | |
|
| 1.0417 | 39.08 | 6800 | 0.2450 | 0.3012 | 0.0711 | |
|
| 1.024 | 41.38 | 7200 | 0.2402 | 0.2956 | 0.0694 | |
|
| 1.0106 | 43.68 | 7600 | 0.2351 | 0.2915 | 0.0681 | |
|
| 1.0014 | 45.98 | 8000 | 0.2328 | 0.2896 | 0.0673 | |
|
| 0.9999 | 48.28 | 8400 | 0.2318 | 0.2866 | 0.0667 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.19.0.dev0 |
|
- Pytorch 1.11.0+cu102 |
|
- Datasets 2.1.1.dev0 |
|
- Tokenizers 0.12.1 |
|
|
