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haris-waqar
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trim-lesson7-classification

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
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  1. README.md +89 -0
  2. best/config.json +336 -0
  3. best/model.safetensors +3 -0
  4. best/preprocessor_config.json +9 -0
  5. best/training_args.bin +3 -0
  6. model.safetensors +1 -1
  7. runs/Nov12_12-52-58_pop-os/events.out.tfevents.1731397979.pop-os +2 -2
README.md ADDED
@@ -0,0 +1,89 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: trim-lesson7-classification
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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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+ # trim-lesson7-classification
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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: 0.1884
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+ - Accuracy: 0.9670
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+ - F1-score: 0.9671
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+ - Recall-score: 0.9670
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+ - Precision-score: 0.9679
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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: 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: 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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+ | 3.8363 | 1.0 | 223 | 3.7557 | 0.1494 | 0.0778 | 0.1494 | 0.0756 |
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+ | 2.7979 | 2.0 | 446 | 2.5827 | 0.6355 | 0.5759 | 0.6355 | 0.6166 |
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+ | 1.6429 | 3.0 | 669 | 1.5768 | 0.9235 | 0.9229 | 0.9235 | 0.9280 |
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+ | 1.659 | 4.0 | 892 | 0.8894 | 0.9440 | 0.9439 | 0.9440 | 0.9461 |
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+ | 0.5305 | 5.0 | 1115 | 0.5156 | 0.9557 | 0.9557 | 0.9557 | 0.9573 |
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+ | 0.3831 | 6.0 | 1338 | 0.3869 | 0.9537 | 0.9539 | 0.9537 | 0.9560 |
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+ | 0.1822 | 7.0 | 1561 | 0.3246 | 0.9576 | 0.9576 | 0.9576 | 0.9589 |
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+ | 0.1308 | 8.0 | 1784 | 0.2840 | 0.9523 | 0.9524 | 0.9523 | 0.9540 |
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+ | 0.1087 | 9.0 | 2007 | 0.3299 | 0.9401 | 0.9393 | 0.9401 | 0.9460 |
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+ | 0.0968 | 10.0 | 2230 | 0.2539 | 0.9548 | 0.9549 | 0.9548 | 0.9571 |
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+ | 0.1088 | 11.0 | 2453 | 0.2290 | 0.9606 | 0.9606 | 0.9606 | 0.9617 |
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+ | 0.7219 | 12.0 | 2676 | 0.2346 | 0.9606 | 0.9607 | 0.9606 | 0.9616 |
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+ | 0.2103 | 13.0 | 2899 | 0.2119 | 0.9629 | 0.9629 | 0.9629 | 0.9640 |
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+ | 0.0414 | 14.0 | 3122 | 0.2431 | 0.9590 | 0.9590 | 0.9590 | 0.9603 |
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+ | 0.9212 | 15.0 | 3345 | 0.2141 | 0.9651 | 0.9651 | 0.9651 | 0.9664 |
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+ | 0.0244 | 16.0 | 3568 | 0.2185 | 0.9620 | 0.9620 | 0.9620 | 0.9633 |
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+ | 0.0468 | 17.0 | 3791 | 0.1949 | 0.9645 | 0.9645 | 0.9645 | 0.9655 |
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+ | 1.2045 | 18.0 | 4014 | 0.1985 | 0.9637 | 0.9637 | 0.9637 | 0.9648 |
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+ | 0.1907 | 19.0 | 4237 | 0.1894 | 0.9634 | 0.9635 | 0.9634 | 0.9646 |
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+ | 0.0185 | 20.0 | 4460 | 0.1956 | 0.9640 | 0.9640 | 0.9640 | 0.9648 |
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+ | 0.0159 | 21.0 | 4683 | 0.2118 | 0.9601 | 0.9601 | 0.9601 | 0.9610 |
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+ | 0.0633 | 22.0 | 4906 | 0.1953 | 0.9634 | 0.9635 | 0.9634 | 0.9646 |
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+ | 0.0244 | 23.0 | 5129 | 0.1915 | 0.9665 | 0.9665 | 0.9665 | 0.9673 |
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+ | 0.008 | 24.0 | 5352 | 0.1842 | 0.9690 | 0.9690 | 0.9690 | 0.9698 |
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+ | 0.2523 | 25.0 | 5575 | 0.1884 | 0.9670 | 0.9671 | 0.9670 | 0.9679 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.1
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+ - Pytorch 2.3.0+cu118
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
best/config.json ADDED
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+ {
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+ "apply_spec_augment": true,
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+ "architectures": [
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+ "Wav2Vec2ForSequenceClassification"
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+ ],
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+ "codevector_dim": 256,
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+ "conv_bias": false,
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+ "ctc_loss_reduction": "sum",
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