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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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- accuracy
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model-index:
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- name: Lesson1results
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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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# Lesson1results
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0149
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- Accuracy: 0.9962
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- F1-score: 0.9962
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- Recall-score: 0.9962
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- Precision-score: 0.9962
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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: 64
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- eval_batch_size: 64
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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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- num_epochs: 20
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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 | Accuracy | F1-score | Recall-score | Precision-score |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------------:|:---------------:|
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| 1.1736 | 1.0 | 278 | 0.9850 | 0.7898 | 0.7552 | 0.7898 | 0.7813 |
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| 0.4185 | 2.0 | 556 | 0.4326 | 0.9106 | 0.8991 | 0.9106 | 0.9062 |
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| 0.3854 | 3.0 | 834 | 0.2507 | 0.9363 | 0.9335 | 0.9363 | 0.9409 |
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| 0.2509 | 4.0 | 1112 | 0.1460 | 0.9666 | 0.9665 | 0.9666 | 0.9673 |
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| 0.107 | 5.0 | 1390 | 0.1278 | 0.9641 | 0.9640 | 0.9641 | 0.9689 |
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| 0.3585 | 6.0 | 1668 | 0.1188 | 0.9758 | 0.9758 | 0.9758 | 0.9764 |
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| 0.2611 | 7.0 | 1946 | 0.1148 | 0.9704 | 0.9702 | 0.9704 | 0.9722 |
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| 0.2493 | 8.0 | 2224 | 0.0638 | 0.9824 | 0.9824 | 0.9824 | 0.9828 |
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| 0.0351 | 9.0 | 2502 | 0.0492 | 0.9887 | 0.9887 | 0.9887 | 0.9890 |
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| 0.4708 | 10.0 | 2780 | 0.0479 | 0.9883 | 0.9883 | 0.9883 | 0.9885 |
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| 0.2958 | 11.0 | 3058 | 0.0561 | 0.9865 | 0.9865 | 0.9865 | 0.9870 |
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| 0.138 | 12.0 | 3336 | 0.0308 | 0.9916 | 0.9916 | 0.9916 | 0.9918 |
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| 0.0525 | 13.0 | 3614 | 0.0226 | 0.9944 | 0.9944 | 0.9944 | 0.9944 |
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| 0.0332 | 14.0 | 3892 | 0.0293 | 0.9916 | 0.9916 | 0.9916 | 0.9920 |
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| 0.0332 | 15.0 | 4170 | 0.0202 | 0.9953 | 0.9953 | 0.9953 | 0.9953 |
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| 0.339 | 16.0 | 4448 | 0.0210 | 0.9955 | 0.9955 | 0.9955 | 0.9955 |
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| 0.211 | 17.0 | 4726 | 0.0218 | 0.9959 | 0.9959 | 0.9959 | 0.9960 |
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| 0.0017 | 18.0 | 5004 | 0.0181 | 0.9964 | 0.9964 | 0.9964 | 0.9964 |
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| 0.1646 | 19.0 | 5282 | 0.0166 | 0.9959 | 0.9959 | 0.9959 | 0.9960 |
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| 0.0014 | 20.0 | 5560 | 0.0149 | 0.9962 | 0.9962 | 0.9962 | 0.9962 |
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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