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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Millad |
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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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# Millad |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.2265 |
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- Wer: 0.5465 |
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- Cer: 0.3162 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 4000 |
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- num_epochs: 750 |
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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 | Cer | |
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|:-------------:|:------:|:-----:|:---------------:|:------:|:------:| |
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| 3.2911 | 33.9 | 2000 | 2.2097 | 0.9963 | 0.6047 | |
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| 1.3419 | 67.8 | 4000 | 1.9042 | 0.7007 | 0.3565 | |
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| 0.6542 | 101.69 | 6000 | 1.7195 | 0.5985 | 0.3194 | |
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| 0.373 | 135.59 | 8000 | 2.2219 | 0.6078 | 0.3241 | |
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| 0.2805 | 169.49 | 10000 | 2.3114 | 0.6320 | 0.3304 | |
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| 0.2014 | 203.39 | 12000 | 2.6898 | 0.6338 | 0.3597 | |
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| 0.1611 | 237.29 | 14000 | 2.7808 | 0.6041 | 0.3379 | |
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| 0.1265 | 271.19 | 16000 | 2.8304 | 0.5632 | 0.3289 | |
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| 0.1082 | 305.08 | 18000 | 2.8373 | 0.5874 | 0.3344 | |
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| 0.103 | 338.98 | 20000 | 2.8580 | 0.5743 | 0.3292 | |
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| 0.0854 | 372.88 | 22000 | 2.5413 | 0.5539 | 0.3186 | |
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| 0.0675 | 406.78 | 24000 | 2.5523 | 0.5502 | 0.3229 | |
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| 0.0531 | 440.68 | 26000 | 2.9369 | 0.5483 | 0.3142 | |
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| 0.0504 | 474.58 | 28000 | 3.1416 | 0.5595 | 0.3225 | |
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| 0.0388 | 508.47 | 30000 | 2.5655 | 0.5390 | 0.3111 | |
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| 0.0396 | 542.37 | 32000 | 3.1923 | 0.5558 | 0.3178 | |
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| 0.0274 | 576.27 | 34000 | 2.9235 | 0.5520 | 0.3257 | |
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| 0.0361 | 610.17 | 36000 | 3.3828 | 0.5762 | 0.3312 | |
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| 0.02 | 644.07 | 38000 | 3.3822 | 0.5874 | 0.3466 | |
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| 0.0176 | 677.97 | 40000 | 3.1191 | 0.5539 | 0.3209 | |
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| 0.0181 | 711.86 | 42000 | 3.2022 | 0.5576 | 0.3237 | |
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| 0.0124 | 745.76 | 44000 | 3.2265 | 0.5465 | 0.3162 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 1.18.3 |
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- Tokenizers 0.12.1 |
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