---
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: 1.0
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# boooooook/finetuned-benben

This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/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