|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-xls-r-300m |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2_XLSR_darija_maroc |
|
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_darija_maroc |
|
|
|
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: 0.2740 |
|
- Wer: 0.3247 |
|
|
|
## 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: 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: 30 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
| 4.9874 | 0.83 | 400 | 2.4916 | 0.9978 | |
|
| 0.9314 | 1.66 | 800 | 0.4379 | 0.5839 | |
|
| 0.4856 | 2.49 | 1200 | 0.3485 | 0.5001 | |
|
| 0.3859 | 3.32 | 1600 | 0.3331 | 0.4768 | |
|
| 0.3271 | 4.15 | 2000 | 0.2932 | 0.4369 | |
|
| 0.2842 | 4.97 | 2400 | 0.2988 | 0.4422 | |
|
| 0.2482 | 5.8 | 2800 | 0.2815 | 0.4174 | |
|
| 0.2252 | 6.63 | 3200 | 0.2967 | 0.4316 | |
|
| 0.2115 | 7.46 | 3600 | 0.2719 | 0.4007 | |
|
| 0.1965 | 8.29 | 4000 | 0.2867 | 0.3985 | |
|
| 0.1823 | 9.12 | 4400 | 0.2744 | 0.4008 | |
|
| 0.1712 | 9.95 | 4800 | 0.2589 | 0.3873 | |
|
| 0.156 | 10.78 | 5200 | 0.2589 | 0.3745 | |
|
| 0.1536 | 11.61 | 5600 | 0.2628 | 0.3799 | |
|
| 0.1404 | 12.44 | 6000 | 0.2704 | 0.3805 | |
|
| 0.1402 | 13.26 | 6400 | 0.2748 | 0.3784 | |
|
| 0.1305 | 14.09 | 6800 | 0.2780 | 0.3769 | |
|
| 0.121 | 14.92 | 7200 | 0.2760 | 0.3698 | |
|
| 0.1147 | 15.75 | 7600 | 0.2723 | 0.3733 | |
|
| 0.1076 | 16.58 | 8000 | 0.2661 | 0.3671 | |
|
| 0.1013 | 17.41 | 8400 | 0.2709 | 0.3665 | |
|
| 0.0964 | 18.24 | 8800 | 0.2748 | 0.3599 | |
|
| 0.0946 | 19.07 | 9200 | 0.2696 | 0.3550 | |
|
| 0.0916 | 19.9 | 9600 | 0.2649 | 0.3596 | |
|
| 0.0849 | 20.73 | 10000 | 0.2905 | 0.3573 | |
|
| 0.0803 | 21.55 | 10400 | 0.2646 | 0.3496 | |
|
| 0.0748 | 22.38 | 10800 | 0.2871 | 0.3486 | |
|
| 0.0739 | 23.21 | 11200 | 0.2751 | 0.3432 | |
|
| 0.0699 | 24.04 | 11600 | 0.2857 | 0.3426 | |
|
| 0.0637 | 24.87 | 12000 | 0.2690 | 0.3377 | |
|
| 0.0627 | 25.7 | 12400 | 0.2737 | 0.3371 | |
|
| 0.0601 | 26.53 | 12800 | 0.2752 | 0.3358 | |
|
| 0.0564 | 27.36 | 13200 | 0.2827 | 0.3329 | |
|
| 0.0536 | 28.19 | 13600 | 0.2764 | 0.3310 | |
|
| 0.0508 | 29.02 | 14000 | 0.2750 | 0.3281 | |
|
| 0.0495 | 29.84 | 14400 | 0.2740 | 0.3247 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.1 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
