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arslanarjumand/wav2vec-reptiles

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: vitouphy/wav2vec2-xls-r-300m-english
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: wav2vec-reptiles
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+ results: []
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+ ---
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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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+
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+ # wav2vec-reptiles
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+
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+ This model is a fine-tuned version of [vitouphy/wav2vec2-xls-r-300m-english](https://huggingface.co/vitouphy/wav2vec2-xls-r-300m-english) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2223.3787
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+ - Pcc Accuracy: 0.2187
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+ - Pcc Fluency: 0.0834
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+ - Pcc Total Score: 0.1532
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+ - Pcc Content: 0.2235
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 6
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.4
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+ - num_epochs: 25
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Pcc Accuracy | Pcc Fluency | Pcc Total Score | Pcc Content |
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+ |:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------:|:---------------:|:-----------:|
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+ | 2728.7846 | 5.0 | 100 | 3196.0576 | 0.3476 | -0.2327 | -0.3110 | 0.2340 |
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+ | 2491.7434 | 10.0 | 200 | 2875.6025 | 0.2791 | -0.0388 | -0.0724 | 0.2475 |
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+ | 1926.2301 | 15.0 | 300 | 2480.8772 | 0.2280 | 0.0499 | 0.1131 | 0.2334 |
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+ | 2065.1381 | 20.0 | 400 | 2265.0391 | 0.2201 | 0.0799 | 0.1478 | 0.2238 |
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+ | 1903.073 | 25.0 | 500 | 2223.3787 | 0.2187 | 0.0834 | 0.1532 | 0.2235 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.0
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+ - Pytorch 2.1.2
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+ - Datasets 2.17.0
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+ - Tokenizers 0.15.1
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