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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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base_model: facebook/wav2vec2-base |
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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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# 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 [MESD](https://huggingface.co/hackathon-pln-es/MESD) 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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This model was trained to classify underlying sentiment of Spanish audio/speech. |
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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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