metadata
library_name: transformers
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- boooooook/benben
metrics:
- accuracy
model-index:
- name: boooooook/finetuned-benben
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: benben
type: boooooook/benben
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 1
boooooook/finetuned-benben
This model is a fine-tuned version of ntu-spml/distilhubert on the benben dataset. It achieves the following results on the evaluation set:
- Loss: 0.0012
- Accuracy: 1.0
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: Use OptimizerNames.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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6001 | 1.0 | 27 | 0.5180 | 0.9583 |
| 0.1095 | 2.0 | 54 | 0.0390 | 1.0 |
| 0.0113 | 3.0 | 81 | 0.0063 | 1.0 |
| 0.0051 | 4.0 | 108 | 0.0032 | 1.0 |
| 0.0034 | 5.0 | 135 | 0.0022 | 1.0 |
| 0.0028 | 6.0 | 162 | 0.0018 | 1.0 |
| 0.0024 | 7.0 | 189 | 0.0015 | 1.0 |
| 0.0022 | 8.0 | 216 | 0.0014 | 1.0 |
| 0.002 | 9.0 | 243 | 0.0013 | 1.0 |
| 0.0019 | 10.0 | 270 | 0.0012 | 1.0 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1