|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-large-xls-r-300m-Arabic-colab |
|
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-large-xls-r-300m-Arabic-colab |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0016 |
|
- Wer: 0.0180 |
|
- Cer: 0.0050 |
|
|
|
## 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: 0.0005 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 6 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 64 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 250 |
|
- num_epochs: 30.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 17.4389 | 1.0 | 51 | 5.2001 | 1.0 | 1.0 | |
|
| 3.9365 | 2.0 | 102 | 3.1379 | 1.0 | 1.0 | |
|
| 3.1693 | 3.0 | 153 | 3.1153 | 1.0 | 1.0 | |
|
| 3.1436 | 4.0 | 204 | 3.0695 | 1.0 | 1.0 | |
|
| 3.0914 | 5.0 | 255 | 2.9734 | 1.0 | 1.0 | |
|
| 2.9509 | 6.0 | 306 | 2.7532 | 1.0 | 1.0 | |
|
| 2.4865 | 7.0 | 357 | 1.8412 | 1.0 | 0.9310 | |
|
| 1.2609 | 8.0 | 408 | 0.3920 | 0.5536 | 0.1712 | |
|
| 0.4001 | 9.0 | 459 | 0.0803 | 0.1065 | 0.0262 | |
|
| 0.1689 | 10.0 | 510 | 0.0340 | 0.0469 | 0.0119 | |
|
| 0.1134 | 11.0 | 561 | 0.0240 | 0.0510 | 0.0150 | |
|
| 0.0756 | 12.0 | 612 | 0.0140 | 0.0355 | 0.0106 | |
|
| 0.0612 | 13.0 | 663 | 0.0098 | 0.0289 | 0.0086 | |
|
| 0.0472 | 14.0 | 714 | 0.0087 | 0.0245 | 0.0066 | |
|
| 0.0443 | 15.0 | 765 | 0.0075 | 0.0242 | 0.0066 | |
|
| 0.0404 | 16.0 | 816 | 0.0072 | 0.0275 | 0.0079 | |
|
| 0.0329 | 17.0 | 867 | 0.0056 | 0.0146 | 0.0040 | |
|
| 0.0322 | 18.0 | 918 | 0.0058 | 0.0165 | 0.0044 | |
|
| 0.0277 | 19.0 | 969 | 0.0056 | 0.0226 | 0.0063 | |
|
| 0.0247 | 20.0 | 1020 | 0.0040 | 0.0180 | 0.0045 | |
|
| 0.0234 | 21.0 | 1071 | 0.0050 | 0.0179 | 0.0052 | |
|
| 0.0186 | 22.0 | 1122 | 0.0034 | 0.0138 | 0.0037 | |
|
| 0.0178 | 23.0 | 1173 | 0.0032 | 0.0139 | 0.0039 | |
|
| 0.0163 | 24.0 | 1224 | 0.0025 | 0.0158 | 0.0042 | |
|
| 0.0165 | 25.0 | 1275 | 0.0023 | 0.0163 | 0.0043 | |
|
| 0.0138 | 26.0 | 1326 | 0.0019 | 0.0141 | 0.0036 | |
|
| 0.0145 | 27.0 | 1377 | 0.0019 | 0.0183 | 0.0047 | |
|
| 0.0128 | 28.0 | 1428 | 0.0019 | 0.0178 | 0.0048 | |
|
| 0.012 | 29.0 | 1479 | 0.0017 | 0.0177 | 0.0048 | |
|
| 0.0121 | 30.0 | 1530 | 0.0016 | 0.0180 | 0.0050 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 1.13.1+cu116 |
|
- Datasets 2.9.0 |
|
- Tokenizers 0.13.2 |
|
|
