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ThuyNT03
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CS337_finetune_wav2vec_base

Audio Classification
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wav2vec2
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End of training

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  1. README.md +23 -23
  2. model.safetensors +1 -1
  3. runs/Dec16_08-00-36_6a0c0cfec2ac/events.out.tfevents.1702713637.6a0c0cfec2ac.905.2 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 1.0701
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- - Accuracy: 0.6599
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  ## Model description
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@@ -37,7 +37,7 @@ More information needed
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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: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -51,26 +51,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 0.97 | 28 | 1.2971 | 0.5876 |
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- | No log | 1.98 | 57 | 1.1261 | 0.6320 |
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- | No log | 2.99 | 86 | 1.0746 | 0.6104 |
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- | 1.156 | 4.0 | 115 | 1.0080 | 0.6396 |
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- | 1.156 | 4.97 | 143 | 0.9706 | 0.6650 |
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- | 1.156 | 5.98 | 172 | 0.9316 | 0.6815 |
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- | 1.156 | 6.99 | 201 | 0.9493 | 0.6662 |
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- | 0.834 | 8.0 | 230 | 0.9774 | 0.6612 |
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- | 0.834 | 8.97 | 258 | 0.9498 | 0.6548 |
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- | 0.834 | 9.98 | 287 | 1.0197 | 0.6472 |
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- | 0.834 | 10.99 | 316 | 0.9520 | 0.6637 |
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- | 0.641 | 12.0 | 345 | 0.9616 | 0.6650 |
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- | 0.641 | 12.97 | 373 | 1.0307 | 0.6523 |
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- | 0.641 | 13.98 | 402 | 1.0298 | 0.6675 |
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- | 0.641 | 14.99 | 431 | 1.0342 | 0.6574 |
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- | 0.4929 | 16.0 | 460 | 1.0520 | 0.6536 |
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- | 0.4929 | 16.97 | 488 | 1.0752 | 0.6472 |
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- | 0.4929 | 17.98 | 517 | 1.0643 | 0.6561 |
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- | 0.4929 | 18.99 | 546 | 1.0709 | 0.6612 |
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- | 0.4929 | 19.48 | 560 | 1.0701 | 0.6599 |
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  ### Framework versions
 
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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: 1.1925
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+ - Accuracy: 0.6574
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.97 | 28 | 2.0354 | 0.1612 |
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+ | No log | 1.98 | 57 | 1.9414 | 0.3769 |
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+ | No log | 2.99 | 86 | 1.7627 | 0.4911 |
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+ | 1.8976 | 4.0 | 115 | 1.6221 | 0.5799 |
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+ | 1.8976 | 4.97 | 143 | 1.5168 | 0.6117 |
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+ | 1.8976 | 5.98 | 172 | 1.4421 | 0.6345 |
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+ | 1.8976 | 6.99 | 201 | 1.3921 | 0.6129 |
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+ | 1.4588 | 8.0 | 230 | 1.3384 | 0.6332 |
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+ | 1.4588 | 8.97 | 258 | 1.3194 | 0.6371 |
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+ | 1.4588 | 9.98 | 287 | 1.2695 | 0.6536 |
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+ | 1.4588 | 10.99 | 316 | 1.2573 | 0.6371 |
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+ | 1.2555 | 12.0 | 345 | 1.2339 | 0.6574 |
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+ | 1.2555 | 12.97 | 373 | 1.2325 | 0.6472 |
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+ | 1.2555 | 13.98 | 402 | 1.2141 | 0.6586 |
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+ | 1.2555 | 14.99 | 431 | 1.2057 | 0.6650 |
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+ | 1.1606 | 16.0 | 460 | 1.2044 | 0.6459 |
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+ | 1.1606 | 16.97 | 488 | 1.2027 | 0.6459 |
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+ | 1.1606 | 17.98 | 517 | 1.1929 | 0.6548 |
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+ | 1.1606 | 18.99 | 546 | 1.1929 | 0.6574 |
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+ | 1.1606 | 19.48 | 560 | 1.1925 | 0.6574 |
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  ### Framework versions
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