metadata
license: apache-2.0
base_model: facebook/hubert-xlarge-ll60k
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: superb_ks_42
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: superb
type: superb
config: ks
split: validation
args: ks
metrics:
- name: Accuracy
type: accuracy
value: 0.9872021182700794
superb_ks_42
This model is a fine-tuned version of facebook/hubert-xlarge-ll60k on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 0.0579
- Accuracy: 0.9872
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: 32
- eval_batch_size: 4
- seed: 42
- 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
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.5639 | 1.0 | 1597 | 0.1012 | 0.9794 |
0.205 | 2.0 | 3194 | 0.0720 | 0.9841 |
0.1774 | 3.0 | 4791 | 0.0664 | 0.9856 |
0.1549 | 4.0 | 6388 | 0.0621 | 0.9856 |
0.1416 | 5.0 | 7985 | 0.0620 | 0.9859 |
0.1328 | 6.0 | 9582 | 0.0614 | 0.9865 |
0.1159 | 7.0 | 11179 | 0.0615 | 0.9865 |
0.1211 | 8.0 | 12776 | 0.0579 | 0.9872 |
0.108 | 9.0 | 14373 | 0.0566 | 0.9863 |
0.1088 | 10.0 | 15970 | 0.0572 | 0.9869 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1