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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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- generated_from_trainer
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model-index:
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- name: wav2vec2-5
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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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# wav2vec2-5
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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: 3.0700
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- Wer: 1.0
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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: 0.003
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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: 400
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- num_epochs: 30
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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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| 3.4082 | 1.37 | 200 | 3.3181 | 1.0 |
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| 2.8798 | 2.74 | 400 | 2.9921 | 1.0 |
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| 2.8703 | 4.11 | 600 | 3.1937 | 1.0 |
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| 2.8643 | 5.48 | 800 | 3.0304 | 1.0 |
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| 2.8655 | 6.85 | 1000 | 3.0321 | 1.0 |
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| 2.8655 | 8.22 | 1200 | 3.0716 | 1.0 |
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| 2.863 | 9.59 | 1400 | 3.1764 | 1.0 |
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| 2.8567 | 10.96 | 1600 | 3.0600 | 1.0 |
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| 2.861 | 12.33 | 1800 | 3.1761 | 1.0 |
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| 2.8606 | 13.7 | 2000 | 3.1028 | 1.0 |
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| 2.8613 | 15.07 | 2200 | 3.2119 | 1.0 |
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| 2.8612 | 16.44 | 2400 | 3.1158 | 1.0 |
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| 2.8603 | 17.81 | 2600 | 3.1230 | 1.0 |
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| 2.8601 | 19.18 | 2800 | 3.0380 | 1.0 |
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| 2.856 | 20.55 | 3000 | 3.0729 | 1.0 |
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| 2.8557 | 21.92 | 3200 | 3.0511 | 1.0 |
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| 2.8556 | 23.29 | 3400 | 3.0710 | 1.0 |
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| 2.8552 | 24.66 | 3600 | 3.1364 | 1.0 |
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| 2.8574 | 26.03 | 3800 | 3.0104 | 1.0 |
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| 2.8543 | 27.4 | 4000 | 3.1068 | 1.0 |
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| 2.8558 | 28.77 | 4200 | 3.0700 | 1.0 |
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### Framework versions
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- Transformers 4.19.2
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- Pytorch 1.11.0+cu113
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- Datasets 2.2.2
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- Tokenizers 0.12.1
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