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wav2vec2-large-robust-ft-libri-960h-finetuned-ravdess-v2
Wiam/wav2vec2-large-robust-ft-libri-960h-finetuned-ravdess-v2
wav2vec2-large-robust-ft-libri-960h-finetuned-ravdess-v2 is a audio classification model from Wiam. 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
- Aug 18, 2023
- Updated
- Aug 18, 2023
- SHA
- d53f41d1
Base models
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-robust-ft-libri-960h-finetuned-ravdess-v2
This model is a fine-tuned version of facebook/wav2vec2-large-robust-ft-libri-960h on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0280
- Accuracy: 0.6146
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 2.0786 | 1.0 | 36 | 2.0692 | 0.1597 |
| 2.0578 | 2.0 | 72 | 2.0555 | 0.1979 |
| 1.9903 | 3.0 | 108 | 1.9172 | 0.2882 |
| 1.8052 | 4.0 | 144 | 1.7975 | 0.2951 |
| 1.7221 | 5.0 | 180 | 1.6602 | 0.4028 |
| 1.5773 | 6.0 | 216 | 1.6362 | 0.4479 |
| 1.4785 | 7.0 | 252 | 1.4675 | 0.4965 |
| 1.3828 | 8.0 | 288 | 1.3735 | 0.5 |
| 1.2352 | 9.0 | 324 | 1.2886 | 0.5278 |
| 1.159 | 10.0 | 360 | 1.2184 | 0.5521 |
| 1.073 | 11.0 | 396 | 1.1456 | 0.5556 |
| 1.0127 | 12.0 | 432 | 1.1864 | 0.5694 |
| 0.9374 | 13.0 | 468 | 1.1865 | 0.5625 |
| 0.8622 | 14.0 | 504 | 1.1745 | 0.5660 |
| 0.8704 | 15.0 | 540 | 1.1563 | 0.5694 |
| 0.8607 | 16.0 | 576 | 1.0466 | 0.5938 |
| 0.8228 | 17.0 | 612 | 1.0457 | 0.6007 |
| 0.8521 | 18.0 | 648 | 1.0280 | 0.6146 |
| 0.8248 | 19.0 | 684 | 1.0399 | 0.6146 |
| 0.7901 | 20.0 | 720 | 1.0402 | 0.6111 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Aug 18, 2023
- Updated
- Aug 18, 2023