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--- |
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tags: |
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- generated_from_trainer |
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base_model: batoula187/wav2vec2-large-xls-r-300m-arabic-colab |
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datasets: |
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- common_voice_12_0 |
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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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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: common_voice_12_0 |
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type: common_voice_12_0 |
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config: ar |
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split: test[:10%] |
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args: ar |
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metrics: |
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- type: wer |
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value: 0.7661710754972002 |
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name: Wer |
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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 [batoula187/wav2vec2-large-xls-r-300m-arabic-colab](https://huggingface.co/batoula187/wav2vec2-large-xls-r-300m-arabic-colab) on the common_voice_12_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0728 |
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- Wer: 0.7662 |
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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: 30 |
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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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| 0.1061 | 2.2599 | 200 | 1.8297 | 0.8034 | |
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| 0.1496 | 4.5198 | 400 | 1.6173 | 0.7955 | |
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| 0.2105 | 6.7797 | 600 | 1.6220 | 0.8040 | |
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| 0.1798 | 9.0395 | 800 | 2.2087 | 0.8405 | |
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| 0.1389 | 11.2994 | 1000 | 1.7900 | 0.7868 | |
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| 0.1143 | 13.5593 | 1200 | 1.7566 | 0.7886 | |
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| 0.103 | 15.8192 | 1400 | 1.8148 | 0.7689 | |
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| 0.0904 | 18.0791 | 1600 | 1.8059 | 0.7627 | |
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| 0.0766 | 20.3390 | 1800 | 2.1398 | 0.7907 | |
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| 0.0682 | 22.5989 | 2000 | 2.0384 | 0.7779 | |
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| 0.0583 | 24.8588 | 2200 | 2.0727 | 0.7658 | |
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| 0.0575 | 27.1186 | 2400 | 2.1649 | 0.7758 | |
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| 0.0582 | 29.3785 | 2600 | 2.0728 | 0.7662 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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