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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-Arabic-phoneme-based-MDD
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
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: 0.7800
- Per: 0.1135
## 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: 40.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Per |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.5228 | 1.0 | 546 | 2.1723 | 0.6314 |
| 1.2389 | 2.0 | 1093 | 0.9571 | 0.2597 |
| 0.7931 | 3.0 | 1640 | 0.8440 | 0.2246 |
| 0.6438 | 4.0 | 2187 | 0.7831 | 0.2045 |
| 0.5584 | 5.0 | 2733 | 0.7660 | 0.1922 |
| 0.5062 | 6.0 | 3280 | 0.7193 | 0.1724 |
| 0.4596 | 7.0 | 3827 | 0.7373 | 0.1720 |
| 0.4227 | 8.0 | 4374 | 0.6829 | 0.1629 |
| 0.3832 | 9.0 | 4920 | 0.7181 | 0.1608 |
| 0.3617 | 10.0 | 5467 | 0.7043 | 0.1591 |
| 0.3495 | 11.0 | 6014 | 0.7295 | 0.1566 |
| 0.3282 | 12.0 | 6561 | 0.6897 | 0.1508 |
| 0.3086 | 13.0 | 7107 | 0.7353 | 0.1554 |
| 0.2911 | 14.0 | 7654 | 0.7144 | 0.1477 |
| 0.2801 | 15.0 | 8201 | 0.6988 | 0.1442 |
| 0.2658 | 16.0 | 8748 | 0.7061 | 0.1475 |
| 0.252 | 17.0 | 9294 | 0.7090 | 0.1403 |
| 0.2487 | 18.0 | 9841 | 0.7032 | 0.1363 |
| 0.2363 | 19.0 | 10388 | 0.7087 | 0.1395 |
| 0.222 | 20.0 | 10935 | 0.6982 | 0.1345 |
| 0.2152 | 21.0 | 11481 | 0.6964 | 0.1361 |
| 0.2063 | 22.0 | 12028 | 0.7246 | 0.1341 |
| 0.1958 | 23.0 | 12575 | 0.7331 | 0.1347 |
| 0.1866 | 24.0 | 13122 | 0.7493 | 0.1326 |
| 0.1786 | 25.0 | 13668 | 0.7536 | 0.1381 |
| 0.1751 | 26.0 | 14215 | 0.7345 | 0.1308 |
| 0.169 | 27.0 | 14762 | 0.7274 | 0.1251 |
| 0.1616 | 28.0 | 15309 | 0.7590 | 0.1293 |
| 0.1589 | 29.0 | 15855 | 0.7330 | 0.1243 |
| 0.1495 | 30.0 | 16402 | 0.7517 | 0.1228 |
| 0.1415 | 31.0 | 16949 | 0.7454 | 0.1208 |
| 0.1376 | 32.0 | 17496 | 0.7827 | 0.1254 |
| 0.1337 | 33.0 | 18042 | 0.7523 | 0.1221 |
| 0.128 | 34.0 | 18589 | 0.7752 | 0.1208 |
| 0.1262 | 35.0 | 19136 | 0.7716 | 0.1174 |
| 0.1196 | 36.0 | 19683 | 0.7620 | 0.1164 |
| 0.1161 | 37.0 | 20229 | 0.7792 | 0.1164 |
| 0.1117 | 38.0 | 20776 | 0.7800 | 0.1140 |
| 0.1103 | 39.0 | 21323 | 0.7716 | 0.1134 |
| 0.1074 | 39.95 | 21840 | 0.7800 | 0.1135 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3
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