|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice_13_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-common_voice_13_0-eo-10 |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: common_voice_13_0 |
|
type: common_voice_13_0 |
|
config: eo |
|
split: validation |
|
args: eo |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.06575168361283507 |
|
--- |
|
|
|
<!-- 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-common_voice_13_0-eo-10 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Cer: 0.0119 |
|
- Loss: 0.0454 |
|
- Wer: 0.0658 |
|
|
|
## 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 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:------:|:---------------:|:------:| |
|
| 2.9894 | 0.22 | 1000 | 1.0 | 2.9257 | 1.0 | |
|
| 0.7104 | 0.44 | 2000 | 0.0457 | 0.2129 | 0.2538 | |
|
| 0.2853 | 0.67 | 3000 | 0.0274 | 0.1109 | 0.1583 | |
|
| 0.2327 | 0.89 | 4000 | 0.0231 | 0.0909 | 0.1320 | |
|
| 0.1917 | 1.11 | 5000 | 0.0206 | 0.0775 | 0.1188 | |
|
| 0.1803 | 1.33 | 6000 | 0.0184 | 0.0698 | 0.1055 | |
|
| 0.1661 | 1.56 | 7000 | 0.0169 | 0.0645 | 0.0961 | |
|
| 0.1635 | 1.78 | 8000 | 0.0170 | 0.0639 | 0.0964 | |
|
| 0.1555 | 2.0 | 9000 | 0.0156 | 0.0592 | 0.0881 | |
|
| 0.1386 | 2.22 | 10000 | 0.0147 | 0.0559 | 0.0821 | |
|
| 0.1338 | 2.45 | 11000 | 0.0146 | 0.0548 | 0.0831 | |
|
| 0.1307 | 2.67 | 12000 | 0.0137 | 0.0529 | 0.0759 | |
|
| 0.1297 | 2.89 | 13000 | 0.0134 | 0.0504 | 0.0745 | |
|
| 0.1201 | 3.11 | 14000 | 0.0131 | 0.0499 | 0.0734 | |
|
| 0.1152 | 3.34 | 15000 | 0.0128 | 0.0484 | 0.0712 | |
|
| 0.1144 | 3.56 | 16000 | 0.0125 | 0.0477 | 0.0695 | |
|
| 0.1179 | 3.78 | 17000 | 0.0122 | 0.0468 | 0.0679 | |
|
| 0.1112 | 4.0 | 18000 | 0.0121 | 0.0468 | 0.0676 | |
|
| 0.1141 | 4.23 | 19000 | 0.0121 | 0.0462 | 0.0668 | |
|
| 0.1085 | 4.45 | 20000 | 0.0119 | 0.0458 | 0.0664 | |
|
| 0.105 | 4.67 | 21000 | 0.0119 | 0.0456 | 0.0660 | |
|
| 0.1072 | 4.89 | 22000 | 0.0119 | 0.0454 | 0.0658 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.29.2 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
|
|
