---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-accents
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.2708333333333333
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilhubert-finetuned-accents

This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0748
- Accuracy: 0.2708

 ## Model description
 - seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.7
- num_epochs: 14
- mixed_precision_training: Native AMP

 ### Training results

 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.4778        | 1.0   | 48   | 2.4807          | 0.0938   |
| 2.4779        | 2.0   | 96   | 2.4651          | 0.1042   |
| 2.4751        | 3.0   | 144  | 2.4365          | 0.1042   |
| 2.3777        | 4.0   | 192  | 2.4187          | 0.1042   |
| 2.3786        | 5.0   | 240  | 2.4050          | 0.1458   |
| 2.3754        | 6.0   | 288  | 2.3446          | 0.1458   |
| 2.1556        | 7.0   | 336  | 2.2284          | 0.2083   |
| 2.1062        | 8.0   | 384  | 2.1533          | 0.2188   |
| 2.0081        | 9.0   | 432  | 2.0765          | 0.2292   |
| 1.813         | 10.0  | 480  | 2.0671          | 0.2083   |
| 1.74          | 11.0  | 528  | 1.9977          | 0.3021   |
| 1.4795        | 12.0  | 576  | 2.0588          | 0.2396   |
| 1.298         | 13.0  | 624  | 2.0652          | 0.3021   |
| 1.2578        | 14.0  | 672  | 2.0748          | 0.2708   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0