metadata
library_name: transformers
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- audio-classification
- generated_from_trainer
datasets:
- common_language
metrics:
- accuracy
model-index:
- name: demo_LID_ntu-spml_distilhubert
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: common_language
type: common_language
config: full
split: validation
args: full
metrics:
- name: Accuracy
type: accuracy
value: 0.6554008152173914
demo_LID_ntu-spml_distilhubert
This model is a fine-tuned version of ntu-spml/distilhubert on the common_language dataset. It achieves the following results on the evaluation set:
- Loss: 2.2545
- Accuracy: 0.6554
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: 8
- eval_batch_size: 1
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: 10.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 9.6557 | 0.9989 | 693 | 2.6549 | 0.2614 |
| 6.1707 | 1.9989 | 1386 | 1.8478 | 0.4681 |
| 3.7871 | 2.9989 | 2079 | 1.6941 | 0.5474 |
| 2.7966 | 3.9989 | 2772 | 1.8580 | 0.5579 |
| 1.5871 | 4.9989 | 3465 | 1.6663 | 0.6140 |
| 0.7355 | 5.9989 | 4158 | 1.9491 | 0.6155 |
| 0.4492 | 6.9989 | 4851 | 2.0594 | 0.6379 |
| 0.1528 | 7.9989 | 5544 | 2.1739 | 0.6403 |
| 0.0468 | 8.9989 | 6237 | 2.3125 | 0.6505 |
| 0.0045 | 9.9989 | 6930 | 2.2545 | 0.6554 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0