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wav2vec2-large-finetuned-iemocap2
Zahra99/wav2vec2-large-finetuned-iemocap2
wav2vec2-large-finetuned-iemocap2 is a audio classification model from Zahra99. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Feb 14, 2023
- Updated
- Feb 14, 2023
- SHA
- c7aae1f8
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
wav2vec2-large-finetuned-iemocap2
This model is a fine-tuned version of facebook/wav2vec2-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2460
- Accuracy: 0.5209
- F1: 0.5049
Model description
More information needed
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: 3e-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 | F1 |
|---|---|---|---|---|---|
| 1.3574 | 0.98 | 25 | 1.4694 | 0.2502 | 0.1002 |
| 1.1919 | 1.98 | 50 | 1.3444 | 0.3754 | 0.3304 |
| 1.1571 | 2.98 | 75 | 1.2644 | 0.4064 | 0.3649 |
| 1.1165 | 3.98 | 100 | 1.1895 | 0.4762 | 0.4223 |
| 1.0498 | 4.98 | 125 | 1.1373 | 0.5053 | 0.4920 |
| 1.0147 | 5.98 | 150 | 1.1089 | 0.5131 | 0.4763 |
| 1.0163 | 6.98 | 175 | 1.1595 | 0.5092 | 0.4651 |
| 0.9711 | 7.98 | 200 | 1.1298 | 0.5179 | 0.4759 |
| 0.9599 | 8.98 | 225 | 1.1460 | 0.5199 | 0.4831 |
| 0.9042 | 9.98 | 250 | 1.1191 | 0.5500 | 0.5307 |
| 0.8734 | 10.98 | 275 | 1.2103 | 0.5364 | 0.4935 |
| 0.8876 | 11.98 | 300 | 1.1837 | 0.5228 | 0.4912 |
| 0.8369 | 12.98 | 325 | 1.2009 | 0.5296 | 0.4927 |
| 0.8357 | 13.98 | 350 | 1.2144 | 0.5238 | 0.5054 |
| 0.8314 | 14.98 | 375 | 1.1866 | 0.5335 | 0.5180 |
| 0.761 | 15.98 | 400 | 1.2145 | 0.5451 | 0.5317 |
| 0.7723 | 16.98 | 425 | 1.2033 | 0.5276 | 0.5073 |
| 0.7775 | 17.98 | 450 | 1.2841 | 0.5228 | 0.4986 |
| 0.7735 | 18.98 | 475 | 1.2249 | 0.5393 | 0.5253 |
| 0.726 | 19.98 | 500 | 1.2460 | 0.5209 | 0.5049 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Feb 14, 2023
- Updated
- Feb 14, 2023