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README.md
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-base
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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: w2v2-base-pretrained_lr1e-4_at0.2_da1
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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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# w2v2-base-pretrained_lr1e-4_at0.2_da1
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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: 5.8341
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- Wer: 1.0477
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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: 32
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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: 1000
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- num_epochs: 60
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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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| 19.6307 | 3.91 | 250 | 4.5235 | 1.0 |
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| 3.3476 | 7.81 | 500 | 3.6749 | 1.0 |
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| 2.8074 | 11.72 | 750 | 2.6368 | 1.0 |
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| 0.5923 | 15.62 | 1000 | 2.6950 | 1.0098 |
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| 0.2651 | 19.53 | 1250 | 3.7328 | 1.0413 |
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| 0.1514 | 23.44 | 1500 | 4.3897 | 1.0520 |
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| 0.0994 | 27.34 | 1750 | 4.4070 | 1.0294 |
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| 0.0682 | 31.25 | 2000 | 4.9965 | 1.0362 |
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| 0.047 | 35.16 | 2250 | 5.0946 | 1.0448 |
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| 0.0375 | 39.06 | 2500 | 5.6089 | 1.0482 |
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| 0.0307 | 42.97 | 2750 | 5.5917 | 1.0409 |
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| 0.0254 | 46.88 | 3000 | 5.5547 | 1.0465 |
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| 0.0195 | 50.78 | 3250 | 5.5936 | 1.0418 |
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| 0.0161 | 54.69 | 3500 | 5.7545 | 1.0431 |
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| 0.0142 | 58.59 | 3750 | 5.8341 | 1.0477 |
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.0.0
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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