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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: xls-r-uyghur-cv8
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-cv8
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2163
- Wer: 0.3241
## 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: 8
- eval_batch_size: 8
- 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: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.2914 | 4.85 | 500 | 3.2283 | 1.0 |
| 3.0068 | 9.71 | 1000 | 2.7939 | 0.9980 |
| 1.4306 | 14.56 | 1500 | 0.4857 | 0.6314 |
| 1.2831 | 19.42 | 2000 | 0.3679 | 0.6066 |
| 1.2065 | 24.27 | 2500 | 0.3303 | 0.5560 |
| 1.1449 | 29.13 | 3000 | 0.3008 | 0.4690 |
| 1.0926 | 33.98 | 3500 | 0.2817 | 0.4619 |
| 1.0635 | 38.83 | 4000 | 0.2665 | 0.4391 |
| 1.029 | 43.69 | 4500 | 0.2616 | 0.4175 |
| 1.0064 | 48.54 | 5000 | 0.2468 | 0.4051 |
| 0.9659 | 53.4 | 5500 | 0.2394 | 0.3860 |
| 0.9254 | 58.25 | 6000 | 0.2373 | 0.3689 |
| 0.9209 | 63.11 | 6500 | 0.2347 | 0.3670 |
| 0.889 | 67.96 | 7000 | 0.2291 | 0.3687 |
| 0.8859 | 72.82 | 7500 | 0.2272 | 0.3616 |
| 0.8441 | 77.67 | 8000 | 0.2232 | 0.3538 |
| 0.8284 | 82.52 | 8500 | 0.2224 | 0.3382 |
| 0.8142 | 87.38 | 9000 | 0.2193 | 0.3310 |
| 0.8012 | 92.23 | 9500 | 0.2168 | 0.3276 |
| 0.7781 | 97.09 | 10000 | 0.2163 | 0.3241 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
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