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: 1.8640
- Accuracy: 0.5225
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 |
---|---|---|---|---|
3.5023 | 1.0 | 200 | 3.4954 | 0.1025 |
3.0745 | 2.0 | 400 | 3.1206 | 0.14 |
2.7667 | 3.0 | 600 | 2.8674 | 0.18 |
2.5477 | 4.0 | 800 | 2.6013 | 0.265 |
2.3458 | 5.0 | 1000 | 2.5071 | 0.3125 |
2.3287 | 6.0 | 1200 | 2.2673 | 0.395 |
1.9078 | 7.0 | 1400 | 2.1068 | 0.4425 |
1.8707 | 8.0 | 1600 | 2.0044 | 0.4775 |
1.7355 | 9.0 | 1800 | 1.8945 | 0.52 |
1.7396 | 10.0 | 2000 | 1.8640 | 0.5225 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1