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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-1b |
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tags: |
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- automatic-speech-recognition |
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- genbed |
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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: xls-r-1b-bem-genbed-f-model |
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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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# xls-r-1b-bem-genbed-f-model |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the GENBED - BEM dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3137 |
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- Wer: 0.5529 |
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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: 30.0 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| No log | 0.2740 | 100 | 3.0378 | 1.0 | |
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| No log | 0.5479 | 200 | 0.8302 | 0.9818 | |
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| No log | 0.8219 | 300 | 0.6783 | 0.9103 | |
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| No log | 1.0959 | 400 | 0.5512 | 0.8721 | |
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| 1.8782 | 1.3699 | 500 | 0.5296 | 0.8568 | |
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| 1.8782 | 1.6438 | 600 | 0.4413 | 0.7333 | |
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| 1.8782 | 1.9178 | 700 | 0.4747 | 0.7614 | |
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| 1.8782 | 2.1918 | 800 | 0.3884 | 0.6667 | |
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| 1.8782 | 2.4658 | 900 | 0.3577 | 0.6355 | |
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| 0.5114 | 2.7397 | 1000 | 0.3585 | 0.6321 | |
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| 0.5114 | 3.0137 | 1100 | 0.3641 | 0.6607 | |
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| 0.5114 | 3.2877 | 1200 | 0.3813 | 0.7282 | |
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| 0.5114 | 3.5616 | 1300 | 0.3829 | 0.7086 | |
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| 0.5114 | 3.8356 | 1400 | 0.3682 | 0.6413 | |
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| 0.3931 | 4.1096 | 1500 | 0.3527 | 0.6221 | |
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| 0.3931 | 4.3836 | 1600 | 0.3481 | 0.6297 | |
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| 0.3931 | 4.6575 | 1700 | 0.3541 | 0.6193 | |
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| 0.3931 | 4.9315 | 1800 | 0.3355 | 0.6242 | |
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| 0.3931 | 5.2055 | 1900 | 0.3339 | 0.5801 | |
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| 0.3293 | 5.4795 | 2000 | 0.3137 | 0.5529 | |
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| 0.3293 | 5.7534 | 2100 | 0.3132 | 0.5822 | |
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| 0.3293 | 6.0274 | 2200 | 0.3145 | 0.5676 | |
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| 0.3293 | 6.3014 | 2300 | 0.3283 | 0.5961 | |
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| 0.3293 | 6.5753 | 2400 | 0.3247 | 0.5988 | |
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### Framework versions |
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- Transformers 4.46.0.dev0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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