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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: facebook/wav2vec2-xls-r-300m
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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-MYST
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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-MYST
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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: nan
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- Wer: 1.0
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- Cer: 1.0005
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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: 4
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- total_train_batch_size: 8
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- total_eval_batch_size: 16
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 15.0
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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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| 3.7175 | 1.1963 | 10000 | inf | 1.0 | 1.0005 |
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| 0.0 | 2.3926 | 20000 | nan | 1.0 | 1.0005 |
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| 0.0 | 3.5889 | 30000 | nan | 1.0 | 1.0005 |
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| 0.0 | 4.7853 | 40000 | nan | 1.0 | 1.0005 |
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| 0.0 | 5.9816 | 50000 | nan | 1.0 | 1.0005 |
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| 0.0 | 7.1779 | 60000 | nan | 1.0 | 1.0005 |
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| 0.0 | 8.3742 | 70000 | nan | 1.0 | 1.0005 |
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| 0.0 | 9.5705 | 80000 | nan | 1.0 | 1.0005 |
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| 0.0 | 10.7668 | 90000 | nan | 1.0 | 1.0005 |
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| 0.0 | 11.9632 | 100000 | nan | 1.0 | 1.0005 |
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| 0.0 | 13.1595 | 110000 | nan | 1.0 | 1.0005 |
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| 0.0 | 14.3558 | 120000 | nan | 1.0 | 1.0005 |
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### Framework versions
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- Transformers 4.48.0.dev0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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