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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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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: wav2vec2-base-timit-demo-google-colab
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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-base-timit-demo-google-colab
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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: 3.0392
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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: 0.001
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- train_batch_size: 8
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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: 150
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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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| 5.2993 | 8.0 | 200 | 3.0327 | 1.0 |
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| 3.0806 | 16.0 | 400 | 3.0476 | 1.0 |
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| 3.0219 | 24.0 | 600 | 3.0472 | 1.0 |
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| 3.0179 | 32.0 | 800 | 3.0435 | 1.0 |
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| 3.0157 | 40.0 | 1000 | 3.0546 | 1.0 |
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| 3.0146 | 48.0 | 1200 | 3.0484 | 1.0 |
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| 3.0139 | 56.0 | 1400 | 3.0344 | 1.0 |
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| 3.0118 | 64.0 | 1600 | 3.0351 | 1.0 |
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| 3.0114 | 72.0 | 1800 | 3.0559 | 1.0 |
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| 3.0114 | 80.0 | 2000 | 3.0526 | 1.0 |
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| 3.0108 | 88.0 | 2200 | 3.0417 | 1.0 |
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| 3.0092 | 96.0 | 2400 | 3.0629 | 1.0 |
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| 3.0089 | 104.0 | 2600 | 3.0352 | 1.0 |
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| 3.0083 | 112.0 | 2800 | 3.0503 | 1.0 |
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| 3.0078 | 120.0 | 3000 | 3.0529 | 1.0 |
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| 3.0072 | 128.0 | 3200 | 3.0378 | 1.0 |
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| 3.0068 | 136.0 | 3400 | 3.0481 | 1.0 |
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| 3.0063 | 144.0 | 3600 | 3.0392 | 1.0 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.3
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- Tokenizers 0.13.3
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