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wavlm-base_4
cloudwalkerw/wavlm-base_4
wavlm-base_4 is a audio classification model from cloudwalkerw. 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
- Sep 28, 2023
- Updated
- Sep 29, 2023
- SHA
- 6e276897
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. -->
wavlm-base_4
This model is a fine-tuned version of microsoft/wavlm-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3325
- F1: 0.9459
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 2
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.3784 | 0.25 | 100 | 0.0784 | 0.9906 |
| 0.1125 | 0.5 | 200 | 0.0638 | 0.9925 |
| 0.1158 | 0.76 | 300 | 0.1716 | 0.9773 |
| 0.327 | 1.01 | 400 | 0.3308 | 0.9459 |
| 0.3346 | 1.26 | 500 | 0.3449 | 0.9459 |
| 0.3345 | 1.51 | 600 | 0.3316 | 0.9459 |
| 0.3313 | 1.76 | 700 | 0.3320 | 0.9459 |
| 0.3249 | 2.02 | 800 | 0.3327 | 0.9459 |
| 0.3403 | 2.27 | 900 | 0.3315 | 0.9459 |
| 0.3345 | 2.52 | 1000 | 0.3382 | 0.9459 |
| 0.3174 | 2.77 | 1100 | 0.3376 | 0.9459 |
| 0.3274 | 3.02 | 1200 | 0.3354 | 0.9459 |
| 0.3296 | 3.28 | 1300 | 0.3307 | 0.9459 |
| 0.3175 | 3.53 | 1400 | 0.3341 | 0.9459 |
| 0.3416 | 3.78 | 1500 | 0.3344 | 0.9459 |
| 0.3412 | 4.03 | 1600 | 0.3308 | 0.9459 |
| 0.3293 | 4.28 | 1700 | 0.3314 | 0.9459 |
| 0.3346 | 4.54 | 1800 | 0.3308 | 0.9459 |
| 0.3279 | 4.79 | 1900 | 0.3317 | 0.9459 |
| 0.3246 | 5.04 | 2000 | 0.3318 | 0.9459 |
| 0.3373 | 5.29 | 2100 | 0.3311 | 0.9459 |
| 0.3262 | 5.55 | 2200 | 0.3335 | 0.9459 |
| 0.3279 | 5.8 | 2300 | 0.3326 | 0.9459 |
| 0.3298 | 6.05 | 2400 | 0.3323 | 0.9459 |
| 0.3397 | 6.3 | 2500 | 0.3311 | 0.9459 |
| 0.3312 | 6.55 | 2600 | 0.3386 | 0.9459 |
| 0.3291 | 6.81 | 2700 | 0.3317 | 0.9459 |
| 0.3146 | 7.06 | 2800 | 0.3323 | 0.9459 |
| 0.3296 | 7.31 | 2900 | 0.3313 | 0.9459 |
| 0.3367 | 7.56 | 3000 | 0.3317 | 0.9459 |
| 0.3232 | 7.81 | 3100 | 0.3318 | 0.9459 |
| 0.3314 | 8.07 | 3200 | 0.3325 | 0.9459 |
| 0.3201 | 8.32 | 3300 | 0.3323 | 0.9459 |
| 0.3301 | 8.57 | 3400 | 0.3347 | 0.9459 |
| 0.3268 | 8.82 | 3500 | 0.3325 | 0.9459 |
| 0.3361 | 9.07 | 3600 | 0.3321 | 0.9459 |
| 0.3395 | 9.33 | 3700 | 0.3313 | 0.9459 |
| 0.3231 | 9.58 | 3800 | 0.3319 | 0.9459 |
| 0.3197 | 9.83 | 3900 | 0.3326 | 0.9459 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.0.post302
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Audio Classification
- Library
- transformers
- Type
- wavlm
- Created
- Sep 28, 2023
- Updated
- Sep 29, 2023