|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-xls-r-300m |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-large-xls-r-300m-Arabic-phoneme-based-MDD-experiment2 |
|
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-phoneme-based-MDD-experiment2 |
|
|
|
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: 0.0434 |
|
- Per: 0.0207 |
|
- Wer: 0.0212 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 6 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- 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: 250 |
|
- num_epochs: 30.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Per | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
|
| 2.4593 | 1.0 | 546 | 1.6587 | 0.9769 | 0.9819 | |
|
| 1.7776 | 2.0 | 1093 | 1.5794 | 0.9995 | 0.9994 | |
|
| 1.733 | 3.0 | 1640 | 1.5264 | 0.9998 | 0.9998 | |
|
| 1.6734 | 4.0 | 2187 | 1.3536 | 0.9948 | 0.9831 | |
|
| 1.5266 | 5.0 | 2733 | 0.8784 | 0.6903 | 0.7321 | |
|
| 1.1705 | 6.0 | 3280 | 0.3408 | 0.2076 | 0.2568 | |
|
| 0.8237 | 7.0 | 3827 | 0.1968 | 0.1045 | 0.1223 | |
|
| 0.66 | 8.0 | 4374 | 0.1400 | 0.0756 | 0.0851 | |
|
| 0.5747 | 9.0 | 4920 | 0.0954 | 0.0665 | 0.0659 | |
|
| 0.5063 | 10.0 | 5467 | 0.0999 | 0.0645 | 0.0650 | |
|
| 0.4641 | 11.0 | 6014 | 0.0800 | 0.0545 | 0.0572 | |
|
| 0.4246 | 12.0 | 6561 | 0.0783 | 0.0512 | 0.0506 | |
|
| 0.3957 | 13.0 | 7107 | 0.0780 | 0.0494 | 0.0516 | |
|
| 0.3693 | 14.0 | 7654 | 0.0647 | 0.0393 | 0.0411 | |
|
| 0.3517 | 15.0 | 8201 | 0.0597 | 0.0364 | 0.0370 | |
|
| 0.3292 | 16.0 | 8748 | 0.0577 | 0.0356 | 0.0361 | |
|
| 0.3079 | 17.0 | 9294 | 0.0573 | 0.0346 | 0.0362 | |
|
| 0.2946 | 18.0 | 9841 | 0.0622 | 0.0350 | 0.0389 | |
|
| 0.2735 | 19.0 | 10388 | 0.0525 | 0.0293 | 0.0300 | |
|
| 0.2588 | 20.0 | 10935 | 0.0553 | 0.0254 | 0.0283 | |
|
| 0.2477 | 21.0 | 11481 | 0.0479 | 0.0244 | 0.0259 | |
|
| 0.2346 | 22.0 | 12028 | 0.0560 | 0.0280 | 0.0283 | |
|
| 0.222 | 23.0 | 12575 | 0.0421 | 0.0242 | 0.0250 | |
|
| 0.208 | 24.0 | 13122 | 0.0508 | 0.0240 | 0.0245 | |
|
| 0.2002 | 25.0 | 13668 | 0.0435 | 0.0218 | 0.0223 | |
|
| 0.1912 | 26.0 | 14215 | 0.0477 | 0.0225 | 0.0239 | |
|
| 0.1823 | 27.0 | 14762 | 0.0414 | 0.0210 | 0.0214 | |
|
| 0.1745 | 28.0 | 15309 | 0.0434 | 0.0212 | 0.0216 | |
|
| 0.1703 | 29.0 | 15855 | 0.0427 | 0.0202 | 0.0212 | |
|
| 0.163 | 29.96 | 16380 | 0.0434 | 0.0207 | 0.0212 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.1 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 1.18.3 |
|
- Tokenizers 0.13.3 |
|
|
