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--- |
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license: apache-2.0 |
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base_model: boumehdi/wav2vec2-large-xlsr-moroccan-darija |
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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-xlsr-moroccan-darija-v2 |
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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-xlsr-moroccan-darija-v2 |
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This model is a fine-tuned version of [boumehdi/wav2vec2-large-xlsr-moroccan-darija](https://huggingface.co/boumehdi/wav2vec2-large-xlsr-moroccan-darija) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2106 |
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- Wer: 0.1908 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 10 |
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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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| 4.8709 | 0.5359 | 500 | 0.4977 | 0.4531 | |
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| 0.4841 | 1.0718 | 1000 | 0.2715 | 0.2724 | |
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| 0.3611 | 1.6077 | 1500 | 0.2311 | 0.2441 | |
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| 0.3088 | 2.1436 | 2000 | 0.2042 | 0.2366 | |
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| 0.2666 | 2.6795 | 2500 | 0.1999 | 0.2352 | |
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| 0.2303 | 3.2154 | 3000 | 0.1900 | 0.2231 | |
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| 0.1921 | 3.7513 | 3500 | 0.1839 | 0.2195 | |
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| 0.1629 | 4.2872 | 4000 | 0.1783 | 0.2153 | |
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| 0.1403 | 4.8232 | 4500 | 0.1904 | 0.2041 | |
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| 0.1178 | 5.3591 | 5000 | 0.1739 | 0.2118 | |
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| 0.1124 | 5.8950 | 5500 | 0.1996 | 0.1970 | |
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| 0.0981 | 6.4309 | 6000 | 0.1890 | 0.2016 | |
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| 0.091 | 6.9668 | 6500 | 0.2020 | 0.1949 | |
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| 0.077 | 7.5027 | 7000 | 0.2057 | 0.1929 | |
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| 0.0769 | 8.0386 | 7500 | 0.2093 | 0.1935 | |
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| 0.0726 | 8.5745 | 8000 | 0.2097 | 0.1924 | |
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| 0.0685 | 9.1104 | 8500 | 0.2088 | 0.1913 | |
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| 0.0625 | 9.6463 | 9000 | 0.2106 | 0.1908 | |
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### Framework versions |
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- Transformers 4.43.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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