---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- audio-classification
- hubert
- esc50
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-esc50-finetuned
  results: []
---

<!-- 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. -->

# hubert-esc50-finetuned

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the ESC-50 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0816
- Accuracy: 0.8325

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.5937        | 1.0   | 200  | 3.4961          | 0.1      |
| 3.1597        | 2.0   | 400  | 3.1798          | 0.1325   |
| 2.8922        | 3.0   | 600  | 2.8387          | 0.2025   |
| 2.6376        | 4.0   | 800  | 2.5594          | 0.285    |
| 2.1292        | 5.0   | 1000 | 2.3671          | 0.35     |
| 2.1607        | 6.0   | 1200 | 2.0533          | 0.4225   |
| 1.7886        | 7.0   | 1400 | 1.8790          | 0.42     |
| 1.626         | 8.0   | 1600 | 1.7147          | 0.52     |
| 1.5246        | 9.0   | 1800 | 1.6021          | 0.545    |
| 0.9318        | 10.0  | 2000 | 1.4441          | 0.5825   |
| 0.9384        | 11.0  | 2200 | 1.2180          | 0.67     |
| 0.9081        | 12.0  | 2400 | 1.1540          | 0.7075   |
| 0.803         | 13.0  | 2600 | 1.1317          | 0.72     |
| 0.4613        | 14.0  | 2800 | 1.0722          | 0.74     |
| 0.4389        | 15.0  | 3000 | 1.1055          | 0.73     |
| 0.4175        | 16.0  | 3200 | 1.0409          | 0.725    |
| 0.2977        | 17.0  | 3400 | 0.9540          | 0.78     |
| 0.3455        | 18.0  | 3600 | 0.9743          | 0.805    |
| 0.2237        | 19.0  | 3800 | 1.0938          | 0.7775   |
| 0.154         | 20.0  | 4000 | 1.0646          | 0.8      |
| 0.0966        | 21.0  | 4200 | 1.0621          | 0.7875   |
| 0.172         | 22.0  | 4400 | 1.1815          | 0.7725   |
| 0.055         | 23.0  | 4600 | 1.1436          | 0.79     |
| 0.1465        | 24.0  | 4800 | 1.1070          | 0.81     |
| 0.0458        | 25.0  | 5000 | 1.1053          | 0.82     |
| 0.0137        | 26.0  | 5200 | 1.0798          | 0.815    |
| 0.0449        | 27.0  | 5400 | 1.1108          | 0.8225   |
| 0.0231        | 28.0  | 5600 | 1.1113          | 0.83     |
| 0.0218        | 29.0  | 5800 | 1.0896          | 0.83     |
| 0.047         | 30.0  | 6000 | 1.0816          | 0.8325   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.1