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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- ml-superb-subset |
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metrics: |
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- wer |
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model-index: |
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- name: fine-tune-wav2vec2-large-xls-r-300m-xty_224s |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: ml-superb-subset |
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type: ml-superb-subset |
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config: xty |
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split: test[:100] |
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args: xty |
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metrics: |
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- name: Wer |
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type: wer |
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value: 1.0584538026398491 |
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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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# fine-tune-wav2vec2-large-xls-r-300m-xty_224s |
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This model was trained from scratch on the ml-superb-subset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7658 |
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- Wer: 1.0585 |
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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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- 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: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 40 |
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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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| 1.5419 | 5.5172 | 400 | 0.4368 | 0.9994 | |
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| 0.423 | 11.0345 | 800 | 0.4315 | 1.0 | |
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| 0.3795 | 16.5517 | 1200 | 0.3892 | 1.0151 | |
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| 0.3306 | 22.0690 | 1600 | 0.4055 | 1.0013 | |
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| 0.2464 | 27.5862 | 2000 | 0.4672 | 1.0421 | |
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| 0.1454 | 33.1034 | 2400 | 0.6656 | 1.0333 | |
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| 0.0883 | 38.6207 | 2800 | 0.7658 | 1.0585 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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