YassineBenlaria
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using niger-mali feature extractor
Browse files- README.md +68 -0
- pytorch_model.bin +1 -1
README.md
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---
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license: apache-2.0
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base_model: jonatasgrosman/wav2vec2-large-xlsr-53-arabic
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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: tamasheq-99-2.feature_ext
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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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# tamasheq-99-2.feature_ext
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This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-arabic](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-arabic) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.9535
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- Wer: 0.9815
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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: 3e-05
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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: 200
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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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| 9.2797 | 15.79 | 300 | 2.8964 | 1.0 |
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| 2.9763 | 31.58 | 600 | 2.7486 | 1.0 |
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| 2.011 | 47.37 | 900 | 1.5549 | 0.9778 |
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| 0.8448 | 63.16 | 1200 | 1.6495 | 0.9852 |
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| 0.6122 | 78.95 | 1500 | 1.7794 | 0.9852 |
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| 0.5039 | 94.74 | 1800 | 1.9535 | 0.9815 |
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### Framework versions
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- Transformers 4.32.1
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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size 1262086317
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