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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: XLS-R_Jibbali_lang |
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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_Jibbali_lang |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1714 |
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- Wer: 0.1941 |
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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: 0.0003 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 20 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 16.1473 | 0.99 | 56 | 11.0651 | 1.0 | |
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| 3.9177 | 2.0 | 113 | 3.4720 | 1.0 | |
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| 3.1902 | 2.99 | 169 | 3.1574 | 1.0 | |
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| 3.1711 | 4.0 | 226 | 3.1379 | 1.0 | |
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| 3.1491 | 4.99 | 282 | 3.1154 | 1.0 | |
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| 3.1449 | 6.0 | 339 | 3.0533 | 1.0 | |
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| 2.9214 | 6.99 | 395 | 2.7533 | 1.0 | |
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| 1.9003 | 8.0 | 452 | 1.4168 | 0.9291 | |
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| 0.6151 | 8.99 | 508 | 0.3110 | 0.3224 | |
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| 0.2125 | 10.0 | 565 | 0.2170 | 0.2145 | |
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| 0.1754 | 10.99 | 621 | 0.1987 | 0.2069 | |
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| 0.1688 | 12.0 | 678 | 0.1870 | 0.1985 | |
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| 0.1012 | 12.99 | 734 | 0.1856 | 0.1908 | |
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| 0.1157 | 14.0 | 791 | 0.1906 | 0.2025 | |
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| 0.1427 | 14.99 | 847 | 0.1844 | 0.1937 | |
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| 0.0513 | 16.0 | 904 | 0.1852 | 0.1915 | |
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| 0.1403 | 16.99 | 960 | 0.1713 | 0.1944 | |
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| 0.1119 | 18.0 | 1017 | 0.1610 | 0.1974 | |
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| 0.1034 | 18.99 | 1073 | 0.1697 | 0.1944 | |
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| 0.0428 | 19.82 | 1120 | 0.1714 | 0.1941 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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