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haris-waqar
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TrimLesson8-9

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
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  1. README.md +89 -0
  2. best/config.json +184 -0
  3. best/label2id.pkl +3 -0
  4. best/model.safetensors +3 -0
  5. best/preprocessor_config.json +9 -0
  6. best/training_args.bin +3 -0
  7. config.json +184 -0
  8. model.safetensors +3 -0
  9. preprocessor_config.json +9 -0
  10. runs/Nov13_12-42-51_HashaamAli/events.out.tfevents.1731483773.HashaamAli.4824.0 +3 -0
  11. runs/Nov13_12-46-34_HashaamAli/events.out.tfevents.1731483995.HashaamAli.8516.0 +3 -0
  12. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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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: TrimLesson8-9
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+ results: []
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+ ---
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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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+
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+ # TrimLesson8-9
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+
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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: 0.0802
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+ - Accuracy: 0.9873
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+ - F1-score: 0.9873
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+ - Recall-score: 0.9873
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+ - Precision-score: 0.9874
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 25
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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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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+ | 2.7148 | 1.0 | 156 | 2.7280 | 0.2544 | 0.1660 | 0.2544 | 0.1877 |
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+ | 1.4541 | 2.0 | 312 | 1.5075 | 0.7997 | 0.7575 | 0.7997 | 0.7669 |
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+ | 0.4792 | 3.0 | 468 | 0.4390 | 0.9650 | 0.9647 | 0.9650 | 0.9667 |
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+ | 0.1559 | 4.0 | 624 | 0.1896 | 0.9666 | 0.9662 | 0.9666 | 0.9701 |
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+ | 0.0931 | 5.0 | 780 | 0.1697 | 0.9626 | 0.9632 | 0.9626 | 0.9659 |
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+ | 0.0333 | 6.0 | 936 | 0.1022 | 0.9793 | 0.9792 | 0.9793 | 0.9806 |
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+ | 0.0114 | 7.0 | 1092 | 0.0693 | 0.9873 | 0.9873 | 0.9873 | 0.9875 |
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+ | 0.0112 | 8.0 | 1248 | 0.0997 | 0.9801 | 0.9798 | 0.9801 | 0.9810 |
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+ | 0.0126 | 9.0 | 1404 | 0.0788 | 0.9849 | 0.9847 | 0.9849 | 0.9855 |
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+ | 0.0052 | 10.0 | 1560 | 0.0661 | 0.9881 | 0.9880 | 0.9881 | 0.9884 |
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+ | 0.0055 | 11.0 | 1716 | 0.0665 | 0.9865 | 0.9865 | 0.9865 | 0.9866 |
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+ | 0.0031 | 12.0 | 1872 | 0.0777 | 0.9849 | 0.9848 | 0.9849 | 0.9853 |
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+ | 0.0036 | 13.0 | 2028 | 0.1021 | 0.9801 | 0.9801 | 0.9801 | 0.9811 |
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+ | 0.0018 | 14.0 | 2184 | 0.1962 | 0.9666 | 0.9662 | 0.9666 | 0.9749 |
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+ | 0.0032 | 15.0 | 2340 | 0.1191 | 0.9809 | 0.9810 | 0.9809 | 0.9814 |
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+ | 0.003 | 16.0 | 2496 | 0.0956 | 0.9817 | 0.9816 | 0.9817 | 0.9819 |
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+ | 0.0017 | 17.0 | 2652 | 0.0735 | 0.9865 | 0.9865 | 0.9865 | 0.9867 |
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+ | 0.0017 | 18.0 | 2808 | 0.0844 | 0.9825 | 0.9825 | 0.9825 | 0.9832 |
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+ | 0.0023 | 19.0 | 2964 | 0.0809 | 0.9881 | 0.9881 | 0.9881 | 0.9883 |
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+ | 0.0019 | 20.0 | 3120 | 0.0932 | 0.9833 | 0.9834 | 0.9833 | 0.9836 |
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+ | 0.0011 | 21.0 | 3276 | 0.0942 | 0.9849 | 0.9849 | 0.9849 | 0.9852 |
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+ | 0.0015 | 22.0 | 3432 | 0.0836 | 0.9857 | 0.9857 | 0.9857 | 0.9859 |
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+ | 0.0013 | 23.0 | 3588 | 0.0929 | 0.9865 | 0.9865 | 0.9865 | 0.9867 |
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+ | 0.0009 | 24.0 | 3744 | 0.0798 | 0.9873 | 0.9873 | 0.9873 | 0.9874 |
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+ | 0.0016 | 25.0 | 3900 | 0.0802 | 0.9873 | 0.9873 | 0.9873 | 0.9874 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.2
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+ - Pytorch 2.5.1+cu118
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+ - Datasets 2.20.0
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+ - Tokenizers 0.20.0
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