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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-Ypause |
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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-Ypause |
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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: 1.3032 |
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- Cer: 30.4276 |
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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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| 8.4175 | 0.2581 | 200 | 3.4467 | 71.5695 | |
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| 1.5788 | 0.5161 | 400 | 2.0587 | 46.5226 | |
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| 1.0864 | 0.7742 | 600 | 1.9065 | 46.5108 | |
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| 0.8759 | 1.0323 | 800 | 1.6587 | 42.8924 | |
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| 0.7067 | 1.2903 | 1000 | 1.4755 | 40.9951 | |
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| 0.615 | 1.5484 | 1200 | 1.6840 | 43.0510 | |
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| 0.5547 | 1.8065 | 1400 | 1.7452 | 43.5620 | |
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| 0.5415 | 2.0645 | 1600 | 1.7313 | 42.6516 | |
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| 0.437 | 2.3226 | 1800 | 1.5706 | 40.1316 | |
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| 0.4045 | 2.5806 | 2000 | 1.2070 | 32.2427 | |
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| 0.3736 | 2.8387 | 2200 | 1.4442 | 37.0007 | |
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| 0.3264 | 3.0968 | 2400 | 1.2398 | 31.9549 | |
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| 0.2651 | 3.3548 | 2600 | 1.4558 | 35.4558 | |
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| 0.2621 | 3.6129 | 2800 | 1.2838 | 32.6363 | |
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| 0.23 | 3.8710 | 3000 | 1.4202 | 33.7935 | |
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| 0.208 | 4.1290 | 3200 | 1.2976 | 31.2970 | |
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| 0.1781 | 4.3871 | 3400 | 1.3553 | 32.2310 | |
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| 0.1628 | 4.6452 | 3600 | 1.3637 | 32.0489 | |
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| 0.1573 | 4.9032 | 3800 | 1.3032 | 30.4276 | |
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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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