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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 |
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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 |
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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: 2.4624 |
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- Accuracy: 0.6620 |
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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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| 1.2041 | 1.0 | 807 | 1.1999 | 0.3662 | |
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| 1.067 | 2.0 | 1614 | 1.4613 | 0.4507 | |
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| 1.1007 | 3.0 | 2421 | 1.5213 | 0.4085 | |
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| 1.1945 | 4.0 | 3228 | 1.6642 | 0.6056 | |
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| 1.3665 | 5.0 | 4035 | 2.9908 | 0.4366 | |
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| 1.4506 | 6.0 | 4842 | 1.9230 | 0.6056 | |
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| 1.495 | 7.0 | 5649 | 1.6813 | 0.6761 | |
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| 1.2605 | 8.0 | 6456 | 1.8937 | 0.6620 | |
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| 1.2713 | 9.0 | 7263 | 1.6284 | 0.6901 | |
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| 1.2608 | 10.0 | 8070 | 1.9438 | 0.6479 | |
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| 1.2068 | 11.0 | 8877 | 1.5237 | 0.7183 | |
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| 1.0478 | 12.0 | 9684 | 2.0007 | 0.6338 | |
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| 1.1282 | 13.0 | 10491 | 1.5307 | 0.7465 | |
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| 0.9433 | 14.0 | 11298 | 2.0042 | 0.6479 | |
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| 0.9574 | 15.0 | 12105 | 2.1985 | 0.6338 | |
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| 0.8737 | 16.0 | 12912 | 2.1568 | 0.6479 | |
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| 0.8937 | 17.0 | 13719 | 2.2980 | 0.6197 | |
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| 0.8681 | 18.0 | 14526 | 2.3268 | 0.6197 | |
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| 0.8005 | 19.0 | 15333 | 2.4827 | 0.6479 | |
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| 0.8176 | 20.0 | 16140 | 2.4842 | 0.6338 | |
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| 0.8133 | 21.0 | 16947 | 2.0620 | 0.6761 | |
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| 0.7404 | 22.0 | 17754 | 2.4148 | 0.6479 | |
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| 0.7134 | 23.0 | 18561 | 2.3389 | 0.6761 | |
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| 0.6573 | 24.0 | 19368 | 2.6972 | 0.6197 | |
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| 0.6848 | 25.0 | 20175 | 2.3375 | 0.6761 | |
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| 0.6161 | 26.0 | 20982 | 2.4791 | 0.6620 | |
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| 0.6301 | 27.0 | 21789 | 2.3807 | 0.6479 | |
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| 0.5758 | 28.0 | 22596 | 2.2243 | 0.6901 | |
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| 0.5598 | 29.0 | 23403 | 2.4130 | 0.6620 | |
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| 0.6066 | 30.0 | 24210 | 2.4624 | 0.6620 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu118 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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