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README.md
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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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