metadata
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- thisisjibon/banglabeats
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-banglabeats
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: BanglaBeats
type: thisisjibon/banglabeats
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.8336425479282622
distilhubert-finetuned-banglabeats
This model is a fine-tuned version of ntu-spml/distilhubert on the BanglaBeats dataset. It achieves the following results on the evaluation set:
- Loss: 1.4126
- Accuracy: 0.8336
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: 6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9439 | 1.0 | 910 | 0.9274 | 0.6425 |
| 0.854 | 2.0 | 1820 | 0.7498 | 0.7260 |
| 0.4835 | 3.0 | 2730 | 0.6329 | 0.7706 |
| 0.6226 | 4.0 | 3640 | 0.6159 | 0.7934 |
| 0.456 | 5.0 | 4550 | 0.7118 | 0.7972 |
| 0.0565 | 6.0 | 5460 | 0.7994 | 0.8052 |
| 0.2605 | 7.0 | 6370 | 0.9735 | 0.8151 |
| 0.3635 | 8.0 | 7280 | 1.0618 | 0.8244 |
| 0.1879 | 9.0 | 8190 | 1.1644 | 0.8213 |
| 0.0292 | 10.0 | 9100 | 1.2543 | 0.8194 |
| 0.0002 | 11.0 | 10010 | 1.4084 | 0.8101 |
| 0.0006 | 12.0 | 10920 | 1.3823 | 0.8132 |
| 0.088 | 13.0 | 11830 | 1.4016 | 0.8256 |
| 0.0381 | 14.0 | 12740 | 1.3587 | 0.8225 |
| 0.0 | 15.0 | 13650 | 1.4242 | 0.8169 |
| 0.0 | 16.0 | 14560 | 1.4053 | 0.8275 |
| 0.0183 | 17.0 | 15470 | 1.4357 | 0.8318 |
| 0.0 | 18.0 | 16380 | 1.4123 | 0.8306 |
| 0.0098 | 19.0 | 17290 | 1.4077 | 0.8330 |
| 0.0 | 20.0 | 18200 | 1.4126 | 0.8336 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3