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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: 0.1752 |
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- Wer: 0.1926 |
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- Cer: 0.0770 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 16.5992 | 0.99 | 56 | 15.4050 | 1.0 | 0.9812 | |
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| 3.79 | 2.0 | 113 | 3.3988 | 1.0 | 0.9812 | |
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| 3.1872 | 2.99 | 169 | 3.1498 | 1.0 | 0.9812 | |
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| 3.1705 | 4.0 | 226 | 3.1354 | 1.0 | 0.9812 | |
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| 3.1147 | 4.99 | 282 | 3.0947 | 1.0 | 0.9812 | |
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| 3.0616 | 6.0 | 339 | 2.9447 | 1.0 | 0.9460 | |
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| 2.8239 | 6.99 | 395 | 2.6661 | 1.0 | 0.9106 | |
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| 1.5494 | 8.0 | 452 | 1.0992 | 0.8684 | 0.3804 | |
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| 0.5291 | 8.99 | 508 | 0.2822 | 0.3026 | 0.1004 | |
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| 0.2022 | 10.0 | 565 | 0.2019 | 0.2080 | 0.0665 | |
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| 0.1721 | 10.99 | 621 | 0.2067 | 0.2032 | 0.0841 | |
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| 0.1705 | 12.0 | 678 | 0.1968 | 0.1996 | 0.0728 | |
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| 0.0989 | 12.99 | 734 | 0.2038 | 0.1955 | 0.0821 | |
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| 0.1299 | 14.0 | 791 | 0.1814 | 0.1963 | 0.0837 | |
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| 0.1352 | 14.99 | 847 | 0.1896 | 0.1941 | 0.0768 | |
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| 0.0487 | 16.0 | 904 | 0.1951 | 0.1933 | 0.0749 | |
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| 0.1412 | 16.99 | 960 | 0.1650 | 0.1970 | 0.0818 | |
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| 0.1027 | 18.0 | 1017 | 0.1720 | 0.1941 | 0.0783 | |
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| 0.0791 | 18.99 | 1073 | 0.1730 | 0.1933 | 0.0767 | |
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| 0.0406 | 19.82 | 1120 | 0.1752 | 0.1926 | 0.0770 | |
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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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