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--- |
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base_model: facebook/wav2vec2-base-960h |
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library_name: transformers |
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license: apache-2.0 |
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metrics: |
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- accuracy |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-base-960h-EMOPIA-10sec |
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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-960h-EMOPIA-10sec |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.5866 |
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- Accuracy: 0.6338 |
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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: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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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: 30 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 1.2014 | 1.0 | 807 | 1.1830 | 0.3662 | |
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| 1.0915 | 2.0 | 1614 | 1.5120 | 0.3239 | |
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| 1.1433 | 3.0 | 2421 | 1.5699 | 0.4085 | |
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| 1.2819 | 4.0 | 3228 | 1.7372 | 0.4789 | |
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| 1.2718 | 5.0 | 4035 | 2.2169 | 0.4648 | |
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| 1.4535 | 6.0 | 4842 | 1.7296 | 0.5775 | |
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| 1.3433 | 7.0 | 5649 | 2.2684 | 0.5493 | |
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| 1.4086 | 8.0 | 6456 | 1.8599 | 0.6479 | |
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| 1.3923 | 9.0 | 7263 | 1.9420 | 0.6197 | |
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| 1.3353 | 10.0 | 8070 | 2.2150 | 0.5775 | |
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| 1.367 | 11.0 | 8877 | 1.9826 | 0.6338 | |
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| 1.1848 | 12.0 | 9684 | 1.9545 | 0.6479 | |
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| 1.1355 | 13.0 | 10491 | 1.9864 | 0.6620 | |
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| 1.1549 | 14.0 | 11298 | 1.9428 | 0.6338 | |
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| 1.0505 | 15.0 | 12105 | 1.9101 | 0.6901 | |
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| 1.0442 | 16.0 | 12912 | 2.1706 | 0.6479 | |
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| 0.9922 | 17.0 | 13719 | 2.4620 | 0.6197 | |
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| 0.8698 | 18.0 | 14526 | 2.1429 | 0.6620 | |
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| 0.8202 | 19.0 | 15333 | 2.3725 | 0.6197 | |
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| 0.8612 | 20.0 | 16140 | 2.1631 | 0.6620 | |
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| 0.8197 | 21.0 | 16947 | 2.3932 | 0.6338 | |
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| 0.7858 | 22.0 | 17754 | 2.2532 | 0.6479 | |
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| 0.7717 | 23.0 | 18561 | 2.8132 | 0.5634 | |
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| 0.6282 | 24.0 | 19368 | 2.5493 | 0.6197 | |
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| 0.7394 | 25.0 | 20175 | 2.3195 | 0.6620 | |
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| 0.5895 | 26.0 | 20982 | 2.4331 | 0.6620 | |
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| 0.5854 | 27.0 | 21789 | 2.4281 | 0.6761 | |
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| 0.6911 | 28.0 | 22596 | 2.4993 | 0.6620 | |
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| 0.5502 | 29.0 | 23403 | 2.6458 | 0.6338 | |
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| 0.584 | 30.0 | 24210 | 2.5866 | 0.6338 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.1+cu118 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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