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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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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-Arabic-colab |
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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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# wav2vec2-large-xls-r-300m-Arabic-colab |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0021 |
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- Wer: 0.0191 |
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- Cer: 0.0072 |
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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: 0.0005 |
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- train_batch_size: 16 |
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- eval_batch_size: 6 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 250 |
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- num_epochs: 30.0 |
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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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| 17.5531 | 1.0 | 51 | 5.2205 | 1.0 | 1.0 | |
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| 3.9441 | 2.0 | 102 | 3.1378 | 1.0 | 1.0 | |
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| 3.1686 | 3.0 | 153 | 3.1191 | 1.0 | 1.0 | |
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| 3.1558 | 4.0 | 204 | 3.1101 | 1.0 | 1.0 | |
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| 3.1286 | 5.0 | 255 | 3.0171 | 1.0 | 1.0 | |
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| 3.0755 | 6.0 | 306 | 2.9542 | 1.0 | 1.0 | |
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| 2.9533 | 7.0 | 357 | 2.8221 | 1.0 | 1.0 | |
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| 2.5924 | 8.0 | 408 | 2.1453 | 1.0 | 0.9771 | |
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| 1.8657 | 9.0 | 459 | 1.1540 | 0.9094 | 0.7057 | |
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| 0.9519 | 10.0 | 510 | 0.4219 | 0.6767 | 0.2782 | |
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| 0.4752 | 11.0 | 561 | 0.1646 | 0.3416 | 0.0870 | |
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| 0.2402 | 12.0 | 612 | 0.0551 | 0.0899 | 0.0255 | |
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| 0.1512 | 13.0 | 663 | 0.0307 | 0.0586 | 0.0167 | |
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| 0.0906 | 14.0 | 714 | 0.0172 | 0.0541 | 0.0161 | |
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| 0.0711 | 15.0 | 765 | 0.0141 | 0.0444 | 0.0125 | |
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| 0.0561 | 16.0 | 816 | 0.0114 | 0.0269 | 0.0065 | |
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| 0.048 | 17.0 | 867 | 0.0090 | 0.0338 | 0.0110 | |
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| 0.0452 | 18.0 | 918 | 0.0072 | 0.0235 | 0.0080 | |
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| 0.0349 | 19.0 | 969 | 0.0073 | 0.0207 | 0.0062 | |
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| 0.0333 | 20.0 | 1020 | 0.0054 | 0.0183 | 0.0055 | |
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| 0.0275 | 21.0 | 1071 | 0.0050 | 0.0280 | 0.0087 | |
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| 0.0262 | 22.0 | 1122 | 0.0039 | 0.0251 | 0.0088 | |
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| 0.0241 | 23.0 | 1173 | 0.0039 | 0.0302 | 0.0110 | |
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| 0.0216 | 24.0 | 1224 | 0.0035 | 0.0243 | 0.0086 | |
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| 0.019 | 25.0 | 1275 | 0.0033 | 0.0250 | 0.0091 | |
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| 0.0178 | 26.0 | 1326 | 0.0027 | 0.0238 | 0.0089 | |
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| 0.0169 | 27.0 | 1377 | 0.0025 | 0.0220 | 0.0080 | |
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| 0.0168 | 28.0 | 1428 | 0.0024 | 0.0175 | 0.0060 | |
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| 0.015 | 29.0 | 1479 | 0.0021 | 0.0194 | 0.0071 | |
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| 0.0131 | 30.0 | 1530 | 0.0021 | 0.0191 | 0.0072 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.0 |
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- Tokenizers 0.13.2 |
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