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update model card README.md
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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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- automatic-speech-recognition
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- librispeech_asr
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- generated_from_trainer
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model-index:
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- name: sew-d-mid-400k-librispeech-clean-100h-ft
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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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# sew-d-mid-400k-librispeech-clean-100h-ft
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This model is a fine-tuned version of [asapp/sew-d-mid-400k](https://huggingface.co/asapp/sew-d-mid-400k) on the LIBRISPEECH_ASR - CLEAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.3540
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- Wer: 1.0536
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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: 3e-05
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- total_train_batch_size: 32
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- total_eval_batch_size: 64
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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: 500
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- num_epochs: 3.0
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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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| 7.319 | 0.11 | 100 | 11.0572 | 1.0 |
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| 3.6726 | 0.22 | 200 | 4.2003 | 1.0 |
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| 2.981 | 0.34 | 300 | 3.5742 | 0.9919 |
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| 2.9411 | 0.45 | 400 | 3.2599 | 1.0 |
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| 2.903 | 0.56 | 500 | 2.9350 | 1.0 |
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| 2.8597 | 0.67 | 600 | 2.9514 | 1.0 |
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| 2.7771 | 0.78 | 700 | 2.8521 | 1.0 |
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| 2.7926 | 0.9 | 800 | 2.7821 | 1.0120 |
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| 2.6623 | 1.01 | 900 | 2.7027 | 0.9924 |
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| 2.5893 | 1.12 | 1000 | 2.6667 | 1.0240 |
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| 2.5733 | 1.23 | 1100 | 2.6341 | 1.0368 |
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| 2.5455 | 1.35 | 1200 | 2.5928 | 1.0411 |
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| 2.4919 | 1.46 | 1300 | 2.5695 | 1.0817 |
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| 2.5182 | 1.57 | 1400 | 2.5559 | 1.1072 |
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| 2.4766 | 1.68 | 1500 | 2.5229 | 1.1257 |
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| 2.4267 | 1.79 | 1600 | 2.4991 | 1.1151 |
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| 2.3919 | 1.91 | 1700 | 2.4768 | 1.1139 |
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| 2.3883 | 2.02 | 1800 | 2.4452 | 1.0636 |
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| 2.3737 | 2.13 | 1900 | 2.4304 | 1.0594 |
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| 2.3569 | 2.24 | 2000 | 2.4095 | 1.0539 |
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| 2.3641 | 2.35 | 2100 | 2.3997 | 1.0511 |
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| 2.3281 | 2.47 | 2200 | 2.3856 | 1.0414 |
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| 2.2912 | 2.58 | 2300 | 2.3750 | 1.0696 |
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| 2.3028 | 2.69 | 2400 | 2.3684 | 1.0436 |
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| 2.2906 | 2.8 | 2500 | 2.3613 | 1.0538 |
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| 2.2822 | 2.91 | 2600 | 2.3558 | 1.0506 |
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### Framework versions
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- Transformers 4.12.0.dev0
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- Pytorch 1.9.0+cu111
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- Datasets 1.13.4.dev0
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- Tokenizers 0.10.3
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