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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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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-1b-E30_fs2 |
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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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# wav2vec2-1b-E30_fs2 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5468 |
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- Cer: 14.2798 |
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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: 0.0001 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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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: 50 |
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- num_epochs: 5 |
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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 | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:-------:| |
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| 10.8739 | 0.2580 | 200 | 2.7757 | 55.2690 | |
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| 1.817 | 0.5160 | 400 | 1.5611 | 35.3031 | |
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| 1.2242 | 0.7741 | 600 | 1.2254 | 29.7404 | |
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| 1.0296 | 1.0321 | 800 | 1.0612 | 26.5508 | |
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| 0.8143 | 1.2901 | 1000 | 1.0154 | 24.8179 | |
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| 0.7274 | 1.5481 | 1200 | 0.9467 | 24.0895 | |
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| 0.6812 | 1.8062 | 1400 | 0.8809 | 23.0204 | |
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| 0.5998 | 2.0642 | 1600 | 1.0420 | 26.1337 | |
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| 0.495 | 2.3222 | 1800 | 0.8705 | 22.3978 | |
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| 0.4552 | 2.5802 | 2000 | 0.8161 | 20.8412 | |
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| 0.4141 | 2.8383 | 2200 | 0.7798 | 20.8999 | |
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| 0.3507 | 3.0963 | 2400 | 0.7629 | 19.4901 | |
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| 0.2985 | 3.3543 | 2600 | 0.6205 | 16.3651 | |
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| 0.2554 | 3.6123 | 2800 | 0.5922 | 15.8952 | |
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| 0.2546 | 3.8703 | 3000 | 0.5993 | 16.0479 | |
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| 0.2114 | 4.1284 | 3200 | 0.5720 | 14.8849 | |
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| 0.1834 | 4.3864 | 3400 | 0.5807 | 15.2491 | |
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| 0.1723 | 4.6444 | 3600 | 0.5454 | 14.1800 | |
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| 0.1631 | 4.9024 | 3800 | 0.5468 | 14.2798 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.3.1.post100 |
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- Datasets 2.19.1 |
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- Tokenizers 0.20.1 |
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