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README.md
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---
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license: cc-by-nc-sa-4.0
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tags:
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- generated_from_trainer
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datasets:
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- marsyas/gtzan
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metrics:
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- accuracy
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model-index:
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- name: wav2vec2-large-robust-12-ft-emotion-msp-dim-finetuned-gtzan
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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-large-robust-12-ft-emotion-msp-dim-finetuned-gtzan
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This model is a fine-tuned version of [audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim](https://huggingface.co/audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7711
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- Accuracy: 0.83
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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: 5e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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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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| 2.186 | 1.0 | 112 | 2.1638 | 0.3 |
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| 1.655 | 2.0 | 225 | 1.7677 | 0.48 |
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| 1.5148 | 3.0 | 337 | 1.3746 | 0.54 |
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| 1.2349 | 4.0 | 450 | 1.1218 | 0.64 |
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| 0.9702 | 5.0 | 562 | 1.0244 | 0.69 |
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| 0.9191 | 6.0 | 675 | 0.9180 | 0.75 |
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| 0.6891 | 7.0 | 787 | 0.8959 | 0.76 |
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| 0.628 | 8.0 | 900 | 0.8084 | 0.81 |
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| 0.7337 | 9.0 | 1012 | 0.7742 | 0.83 |
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| 0.5573 | 9.96 | 1120 | 0.7711 | 0.83 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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