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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- common_voice
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model-index:
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- name: xls-r-kyrgiz-cv8
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# xls-r-kyrgiz-cv8
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.5495
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- Wer: 0.2951
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- Cer: 0.0789
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 32
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 300.0
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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| 3.1079 | 18.51 | 500 | 2.6795 | 0.9996 | 0.9825 |
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| 0.8506 | 37.04 | 1000 | 0.4323 | 0.3718 | 0.0961 |
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| 0.6821 | 55.55 | 1500 | 0.4105 | 0.3311 | 0.0878 |
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| 0.6091 | 74.07 | 2000 | 0.4281 | 0.3168 | 0.0851 |
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| 0.5429 | 92.58 | 2500 | 0.4525 | 0.3147 | 0.0842 |
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| 0.5063 | 111.11 | 3000 | 0.4619 | 0.3144 | 0.0839 |
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| 0.4661 | 129.62 | 3500 | 0.4660 | 0.3039 | 0.0818 |
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| 0.4353 | 148.15 | 4000 | 0.4695 | 0.3083 | 0.0820 |
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| 0.4048 | 166.65 | 4500 | 0.4909 | 0.3085 | 0.0824 |
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| 0.3852 | 185.18 | 5000 | 0.5074 | 0.3048 | 0.0812 |
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| 0.3567 | 203.69 | 5500 | 0.5111 | 0.3012 | 0.0810 |
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| 0.3451 | 222.22 | 6000 | 0.5225 | 0.2982 | 0.0804 |
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| 0.325 | 240.73 | 6500 | 0.5270 | 0.2955 | 0.0796 |
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| 0.3089 | 259.25 | 7000 | 0.5381 | 0.2929 | 0.0793 |
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| 0.2941 | 277.76 | 7500 | 0.5565 | 0.2923 | 0.0794 |
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| 0.2945 | 296.29 | 8000 | 0.5495 | 0.2951 | 0.0789 |
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### Framework versions
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- Transformers 4.17.0.dev0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.3
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- Tokenizers 0.11.0
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