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wavlm-basic_s-r-5c_8batch_5sec_0.0001lr_unfrozen
reralle/wavlm-basic_s-r-5c_8batch_5sec_0.0001lr_unfrozen
wavlm-basic_s-r-5c_8batch_5sec_0.0001lr_unfrozen is a audio classification model from reralle. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- Model type
- wavlm
- Access
- Public
- Created
- Apr 30, 2023
- Updated
- Apr 30, 2023
- SHA
- 74574540
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. -->
wavlm-basic_s-r-5c_8batch_5sec_0.0001lr_unfrozen
This model is a fine-tuned version of microsoft/wavlm-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9859
- Accuracy: 0.75
- F1: 0.7515
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: 0.0001
- 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: 0.003
- num_epochs: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 2.2767 | 0.33 | 78 | 2.3002 | 0.1 | 0.0182 |
| 2.0686 | 0.66 | 156 | 2.4001 | 0.1 | 0.0182 |
| 1.7043 | 0.99 | 234 | 2.1688 | 0.19 | 0.0875 |
| 1.6238 | 1.32 | 312 | 2.0125 | 0.2533 | 0.1313 |
| 1.4339 | 1.65 | 390 | 1.7132 | 0.4433 | 0.3567 |
| 1.2106 | 1.97 | 468 | 1.6403 | 0.5233 | 0.4524 |
| 1.0918 | 2.3 | 546 | 1.6254 | 0.58 | 0.5063 |
| 0.9621 | 2.63 | 624 | 1.3746 | 0.5967 | 0.5248 |
| 0.8272 | 2.96 | 702 | 1.1466 | 0.6333 | 0.5852 |
| 0.8004 | 3.29 | 780 | 1.0567 | 0.6633 | 0.5944 |
| 0.676 | 3.62 | 858 | 0.9788 | 0.6967 | 0.6457 |
| 0.6323 | 3.95 | 936 | 0.9743 | 0.7133 | 0.6946 |
| 0.609 | 4.28 | 1014 | 1.0422 | 0.6967 | 0.6768 |
| 0.6942 | 4.61 | 1092 | 1.1858 | 0.6833 | 0.6661 |
| 0.5759 | 4.94 | 1170 | 1.1483 | 0.7233 | 0.7183 |
| 0.4296 | 5.27 | 1248 | 1.0037 | 0.73 | 0.7224 |
| 0.4322 | 5.59 | 1326 | 0.7829 | 0.8067 | 0.8046 |
| 0.4092 | 5.92 | 1404 | 0.8609 | 0.7767 | 0.7743 |
| 0.352 | 6.25 | 1482 | 1.1247 | 0.72 | 0.7128 |
| 0.2858 | 6.58 | 1560 | 0.9369 | 0.76 | 0.7500 |
| 0.2945 | 6.91 | 1638 | 1.2018 | 0.7267 | 0.7083 |
| 0.329 | 7.24 | 1716 | 0.9690 | 0.7767 | 0.7786 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Audio Classification
- Library
- transformers
- Type
- wavlm
- Created
- Apr 30, 2023
- Updated
- Apr 30, 2023