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---
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license: apache-2.0
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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: wav2vec2-base-finetuned-sentiment-mesd
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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-finetuned-sentiment-mesd
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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: 0.5729
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- Accuracy: 0.8308
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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: 1.25e-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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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: 20
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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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| No log | 1.0 | 7 | 0.5729 | 0.8308 |
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| No log | 2.0 | 14 | 0.6577 | 0.8 |
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| 0.1602 | 3.0 | 21 | 0.7055 | 0.8 |
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| 0.1602 | 4.0 | 28 | 0.8696 | 0.7615 |
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| 0.1602 | 5.0 | 35 | 0.6807 | 0.7923 |
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| 0.1711 | 6.0 | 42 | 0.7303 | 0.7923 |
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| 0.1711 | 7.0 | 49 | 0.7028 | 0.8077 |
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| 0.1711 | 8.0 | 56 | 0.7368 | 0.8 |
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| 0.1608 | 9.0 | 63 | 0.7190 | 0.7923 |
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| 0.1608 | 10.0 | 70 | 0.6913 | 0.8077 |
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| 0.1608 | 11.0 | 77 | 0.7047 | 0.8077 |
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| 0.1753 | 12.0 | 84 | 0.6801 | 0.8 |
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| 0.1753 | 13.0 | 91 | 0.7208 | 0.7769 |
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| 0.1753 | 14.0 | 98 | 0.7458 | 0.7846 |
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| 0.203 | 15.0 | 105 | 0.6494 | 0.8077 |
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| 0.203 | 16.0 | 112 | 0.6256 | 0.8231 |
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| 0.203 | 17.0 | 119 | 0.6788 | 0.8 |
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| 0.1919 | 18.0 | 126 | 0.6757 | 0.7846 |
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| 0.1919 | 19.0 | 133 | 0.6859 | 0.7846 |
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| 0.1641 | 20.0 | 140 | 0.6832 | 0.7846 |
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### Framework versions
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- Transformers 4.11.3
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- Pytorch 1.10.0+cu111
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- Datasets 2.0.0
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- Tokenizers 0.10.3
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