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---
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tags:
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- generated_from_trainer
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model-index:
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- name: wav2vec2-onomatopoeia-finetune_smalldata_ESC50pretrained_3
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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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# wav2vec2-onomatopoeia-finetune_smalldata_ESC50pretrained_3
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This model is a fine-tuned version of [/root/workspace/wav2vec2-pretrained_with_ESC50_10000epochs_32batch_2022-07-09_22-16-46/pytorch_model.bin](https://huggingface.co//root/workspace/wav2vec2-pretrained_with_ESC50_10000epochs_32batch_2022-07-09_22-16-46/pytorch_model.bin) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5350
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- Cer: 1.2730
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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: 64
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- eval_batch_size: 16
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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: 1000
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- num_epochs: 30
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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 | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 4.4243 | 4.67 | 500 | 2.6901 | 1.1259 |
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| 2.4282 | 9.35 | 1000 | 2.7495 | 1.1563 |
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| 2.3377 | 14.02 | 1500 | 2.2475 | 0.9617 |
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| 2.2434 | 18.69 | 2000 | 2.2765 | 1.1908 |
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| 2.2731 | 23.36 | 2500 | 2.2574 | 1.1669 |
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| 2.3436 | 28.04 | 3000 | 2.5350 | 1.2730 |
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### Framework versions
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- Transformers 4.11.3
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- Pytorch 1.9.1+cu111
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- Datasets 1.13.3
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- Tokenizers 0.10.3
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