metadata
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- audio-classification
- hubert
- esc50
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-esc50-finetuned-v2
results: []
hubert-esc50-finetuned-v2
This model is a fine-tuned version of facebook/hubert-base-ls960 on the ESC-50 dataset. It achieves the following results on the evaluation set:
- Loss: 2.0573
- Accuracy: 0.46
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.6034 | 1.0 | 200 | 3.6057 | 0.0725 |
| 3.2797 | 2.0 | 400 | 3.2749 | 0.095 |
| 2.9855 | 3.0 | 600 | 3.0805 | 0.1525 |
| 2.807 | 4.0 | 800 | 2.7985 | 0.2225 |
| 2.5864 | 5.0 | 1000 | 2.5974 | 0.2825 |
| 2.4893 | 6.0 | 1200 | 2.3808 | 0.34 |
| 2.1716 | 7.0 | 1400 | 2.2675 | 0.3475 |
| 2.0351 | 8.0 | 1600 | 2.1746 | 0.3925 |
| 1.9235 | 9.0 | 1800 | 2.0876 | 0.4325 |
| 1.9286 | 10.0 | 2000 | 2.0573 | 0.46 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1