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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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metrics:
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- wer
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model-index:
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- name: dgx2_whisper_base_distil_att_loss_mozilla_epochs_40_batch_16_concat_dataset
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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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# dgx2_whisper_base_distil_att_loss_mozilla_epochs_40_batch_16_concat_dataset
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This model is a fine-tuned version of [rohitp1/dgx1_whisper_base_finetune_teacher_babble_noise_mozilla_100_epochs_batch_16](https://huggingface.co/rohitp1/dgx1_whisper_base_finetune_teacher_babble_noise_mozilla_100_epochs_batch_16) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.1315
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- Wer: 30.6873
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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: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 128
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- total_train_batch_size: 2048
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine_with_restarts
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- lr_scheduler_warmup_ratio: 0.2
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- num_epochs: 40
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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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| 2.182 | 2.2 | 150 | 2.1102 | 31.0198 |
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| 2.0124 | 4.41 | 300 | 2.0539 | 30.7134 |
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| 1.9833 | 6.61 | 450 | 2.0528 | 30.7099 |
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| 1.9666 | 8.82 | 600 | 2.0768 | 30.6490 |
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| 1.9756 | 11.03 | 750 | 2.0959 | 30.6699 |
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| 1.9659 | 13.23 | 900 | 2.1110 | 30.6612 |
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| 1.9583 | 15.44 | 1050 | 2.1150 | 30.6403 |
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| 1.9524 | 17.64 | 1200 | 2.1191 | 30.6507 |
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| 1.9461 | 19.85 | 1350 | 2.1222 | 30.6716 |
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| 1.9448 | 22.06 | 1500 | 2.1275 | 30.6890 |
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| 1.9393 | 24.26 | 1650 | 2.1297 | 30.6646 |
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| 1.935 | 26.47 | 1800 | 2.1315 | 30.6873 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.12.1
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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