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---
language:
- ug
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_11_0
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: xls-r-uyghur-cv11
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. -->
# xls-r-uyghur-cv11
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_11_0 - UG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2191
- Wer: 0.3257
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- 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: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.3958 | 4.36 | 500 | 3.3137 | 1.0 |
| 3.032 | 8.71 | 1000 | 2.8586 | 0.9993 |
| 1.3977 | 13.07 | 1500 | 0.4786 | 0.6375 |
| 1.2751 | 17.43 | 2000 | 0.3816 | 0.5393 |
| 1.2113 | 21.79 | 2500 | 0.3451 | 0.5099 |
| 1.156 | 26.14 | 3000 | 0.3245 | 0.4919 |
| 1.1226 | 30.5 | 3500 | 0.2992 | 0.4441 |
| 1.0913 | 34.86 | 4000 | 0.2831 | 0.4315 |
| 1.0615 | 39.22 | 4500 | 0.2808 | 0.4340 |
| 1.0455 | 43.57 | 5000 | 0.2713 | 0.4088 |
| 1.0228 | 47.93 | 5500 | 0.2622 | 0.3960 |
| 0.9936 | 52.29 | 6000 | 0.2525 | 0.3796 |
| 0.968 | 56.64 | 6500 | 0.2506 | 0.3798 |
| 0.9704 | 61.0 | 7000 | 0.2481 | 0.3735 |
| 0.9552 | 65.36 | 7500 | 0.2394 | 0.3643 |
| 0.9417 | 69.72 | 8000 | 0.2350 | 0.3537 |
| 0.9215 | 74.07 | 8500 | 0.2326 | 0.3507 |
| 0.9097 | 78.43 | 9000 | 0.2277 | 0.3487 |
| 0.9003 | 82.79 | 9500 | 0.2230 | 0.3362 |
| 0.8857 | 87.15 | 10000 | 0.2246 | 0.3362 |
| 0.882 | 91.5 | 10500 | 0.2236 | 0.3315 |
| 0.8719 | 95.86 | 11000 | 0.2203 | 0.3271 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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