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wav2vec2-base-finetuned-sentiment-mesd
somosnlp-hackathon-2022/wav2vec2-base-finetuned-sentiment-mesd
wav2vec2-base-finetuned-sentiment-mesd is a audio classification model from somosnlp-hackathon-2022. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
This model is a fine-tuned version of facebook/wav2vec2-base on the MESD dataset. It achieves the following results on the evaluation set: - Loss: 0.5729 - Accuracy: 0.8308
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At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Mar 27, 2022
- Updated
- Dec 20, 2023
- SHA
- 9bc54869
Base models
Model card
From the Hugging Face model README
wav2vec2-base-finetuned-sentiment-mesd
This model is a fine-tuned version of facebook/wav2vec2-base on the MESD dataset. It achieves the following results on the evaluation set:
- Loss: 0.5729
- Accuracy: 0.8308
Model description
This model was trained to classify underlying sentiment of Spanish audio/speech.
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.25e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 7 | 0.5729 | 0.8308 |
| No log | 2.0 | 14 | 0.6577 | 0.8 |
| 0.1602 | 3.0 | 21 | 0.7055 | 0.8 |
| 0.1602 | 4.0 | 28 | 0.8696 | 0.7615 |
| 0.1602 | 5.0 | 35 | 0.6807 | 0.7923 |
| 0.1711 | 6.0 | 42 | 0.7303 | 0.7923 |
| 0.1711 | 7.0 | 49 | 0.7028 | 0.8077 |
| 0.1711 | 8.0 | 56 | 0.7368 | 0.8 |
| 0.1608 | 9.0 | 63 | 0.7190 | 0.7923 |
| 0.1608 | 10.0 | 70 | 0.6913 | 0.8077 |
| 0.1608 | 11.0 | 77 | 0.7047 | 0.8077 |
| 0.1753 | 12.0 | 84 | 0.6801 | 0.8 |
| 0.1753 | 13.0 | 91 | 0.7208 | 0.7769 |
| 0.1753 | 14.0 | 98 | 0.7458 | 0.7846 |
| 0.203 | 15.0 | 105 | 0.6494 | 0.8077 |
| 0.203 | 16.0 | 112 | 0.6256 | 0.8231 |
| 0.203 | 17.0 | 119 | 0.6788 | 0.8 |
| 0.1919 | 18.0 | 126 | 0.6757 | 0.7846 |
| 0.1919 | 19.0 | 133 | 0.6859 | 0.7846 |
| 0.1641 | 20.0 | 140 | 0.6832 | 0.7846 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.10.3
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Mar 27, 2022
- Updated
- Dec 20, 2023