Downloads · 30 days
11
3% of all-time downloads
finetuned_wav2vec2.0-base-on-IEMOCAP_3
minoosh/finetuned_wav2vec2.0-base-on-IEMOCAP_3
finetuned_wav2vec2.0-base-on-IEMOCAP_3 is a audio classification model from minoosh. 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. --
All-time downloads
384
Public
Repo size
6.1 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin378 MB · 100%
At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Jun 10, 2023
- Updated
- Jun 10, 2023
- SHA
- 9334c229
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. -->
finetuned_wav2vec2.0-base-on-IEMOCAP_3
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3119
- Accuracy: 0.6412
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: 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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.197 | 1.0 | 109 | 1.1517 | 0.4738 |
| 0.9312 | 2.0 | 219 | 0.9722 | 0.5774 |
| 0.8183 | 3.0 | 328 | 0.8322 | 0.6640 |
| 0.7456 | 4.0 | 438 | 0.7201 | 0.7198 |
| 0.599 | 5.0 | 547 | 0.7853 | 0.7118 |
| 0.4166 | 6.0 | 657 | 0.6359 | 0.7711 |
| 0.2507 | 7.0 | 766 | 0.7845 | 0.7415 |
| 0.2794 | 8.0 | 876 | 0.8188 | 0.7494 |
| 0.1777 | 9.0 | 985 | 0.7406 | 0.7950 |
| 0.1344 | 10.0 | 1095 | 0.8735 | 0.7620 |
| 0.0719 | 11.0 | 1204 | 0.9456 | 0.7688 |
| 0.0577 | 12.0 | 1314 | 0.9727 | 0.7768 |
| 0.0405 | 13.0 | 1423 | 1.0440 | 0.7756 |
| 0.0619 | 14.0 | 1533 | 1.0239 | 0.7813 |
| 0.0299 | 14.93 | 1635 | 1.0343 | 0.7790 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Jun 10, 2023
- Updated
- Jun 10, 2023