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w2v-bert-2.0-DF-3.0
DavidCombei/w2v-bert-2.0-DF-3.0
w2v-bert-2.0-DF-3.0 is a audio classification model from DavidCombei. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- mit
- Model type
- wav2vec2-bert
- Access
- Public
- Created
- Nov 22, 2024
- Updated
- Nov 22, 2024
- SHA
- 73916f3a
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. -->
w2v-bert-2.0-DF-3.0
This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2216
- Accuracy: 0.9596
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: 42
- eval_batch_size: 42
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 168
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0314 | 1.0 | 299 | 0.2092 | 0.9542 |
| 0.0078 | 2.0 | 598 | 0.2216 | 0.9596 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.0a0+e000cf0ad9.nv24.10
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2-bert
- License
- mit
- Created
- Nov 22, 2024
- Updated
- Nov 22, 2024