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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-large-xlsr-53 |
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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: xlsr-no-mi-nmcpc |
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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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# xlsr-no-mi-nmcpc |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0001 |
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- Wer: 0.2617 |
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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: 0.0004 |
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- train_batch_size: 8 |
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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: 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: 132 |
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- num_epochs: 100 |
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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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| 4.8152 | 3.8835 | 200 | 3.0388 | 1.0 | |
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| 2.9502 | 7.7670 | 400 | 2.6587 | 1.0 | |
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| 2.233 | 11.6505 | 600 | 0.8485 | 0.7638 | |
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| 0.8492 | 15.5340 | 800 | 0.1759 | 0.4319 | |
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| 0.3659 | 19.4175 | 1000 | 0.0757 | 0.3489 | |
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| 0.2237 | 23.3010 | 1200 | 0.0338 | 0.3064 | |
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| 0.1608 | 27.1845 | 1400 | 0.0238 | 0.3 | |
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| 0.1265 | 31.0680 | 1600 | 0.0142 | 0.2766 | |
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| 0.0989 | 34.9515 | 1800 | 0.0145 | 0.2766 | |
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| 0.0803 | 38.8350 | 2000 | 0.0043 | 0.2681 | |
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| 0.0701 | 42.7184 | 2200 | 0.0032 | 0.2638 | |
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| 0.061 | 46.6019 | 2400 | 0.0022 | 0.2638 | |
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| 0.0507 | 50.4854 | 2600 | 0.0033 | 0.2702 | |
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| 0.0422 | 54.3689 | 2800 | 0.0054 | 0.2660 | |
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| 0.0382 | 58.2524 | 3000 | 0.0011 | 0.2553 | |
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| 0.0381 | 62.1359 | 3200 | 0.0032 | 0.2660 | |
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| 0.0332 | 66.0194 | 3400 | 0.0006 | 0.2574 | |
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| 0.025 | 69.9029 | 3600 | 0.0007 | 0.2596 | |
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| 0.0185 | 73.7864 | 3800 | 0.0002 | 0.2596 | |
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| 0.0169 | 77.6699 | 4000 | 0.0003 | 0.2617 | |
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| 0.0136 | 81.5534 | 4200 | 0.0003 | 0.2617 | |
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| 0.0166 | 85.4369 | 4400 | 0.0002 | 0.2617 | |
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| 0.0124 | 89.3204 | 4600 | 0.0001 | 0.2617 | |
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| 0.0114 | 93.2039 | 4800 | 0.0001 | 0.2617 | |
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| 0.0115 | 97.0874 | 5000 | 0.0001 | 0.2617 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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