---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: urdu-emotions-hubert-large-Emotion
  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: 0.8166666666666667
---

<!-- 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. -->

# urdu-emotions-hubert-large-Emotion

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3374
- Accuracy: 0.8167

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 60

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9333  | 7    | 0.9539          | 0.7833   |
| 0.1337        | 2.0     | 15   | 0.8845          | 0.8167   |
| 0.1048        | 2.9333  | 22   | 1.0824          | 0.75     |
| 0.0406        | 4.0     | 30   | 1.0672          | 0.8      |
| 0.0406        | 4.9333  | 37   | 1.2542          | 0.75     |
| 0.0931        | 6.0     | 45   | 0.9778          | 0.8      |
| 0.0646        | 6.9333  | 52   | 1.2557          | 0.75     |
| 0.0966        | 8.0     | 60   | 1.0541          | 0.7833   |
| 0.0966        | 8.9333  | 67   | 1.5521          | 0.75     |
| 0.1301        | 10.0    | 75   | 0.9688          | 0.8333   |
| 0.2704        | 10.9333 | 82   | 1.2517          | 0.7667   |
| 0.1625        | 12.0    | 90   | 1.3938          | 0.7667   |
| 0.1625        | 12.9333 | 97   | 1.4804          | 0.7667   |
| 0.1278        | 14.0    | 105  | 0.9219          | 0.8167   |
| 0.2052        | 14.9333 | 112  | 1.2735          | 0.75     |
| 0.2487        | 16.0    | 120  | 1.0251          | 0.7833   |
| 0.2487        | 16.9333 | 127  | 1.1808          | 0.8      |
| 0.1784        | 18.0    | 135  | 1.2522          | 0.7333   |
| 0.2182        | 18.9333 | 142  | 0.8958          | 0.8333   |
| 0.1688        | 20.0    | 150  | 1.1747          | 0.75     |
| 0.1688        | 20.9333 | 157  | 1.3938          | 0.8      |
| 0.2948        | 22.0    | 165  | 0.6410          | 0.8833   |
| 0.0945        | 22.9333 | 172  | 0.8846          | 0.8333   |
| 0.0738        | 24.0    | 180  | 0.7653          | 0.8333   |
| 0.0738        | 24.9333 | 187  | 0.7587          | 0.8333   |
| 0.0909        | 26.0    | 195  | 1.1861          | 0.8      |
| 0.0721        | 26.9333 | 202  | 0.8185          | 0.8333   |
| 0.1215        | 28.0    | 210  | 1.4169          | 0.7333   |
| 0.1215        | 28.9333 | 217  | 1.1844          | 0.8      |
| 0.0454        | 30.0    | 225  | 1.1273          | 0.7833   |
| 0.0915        | 30.9333 | 232  | 1.3536          | 0.8      |
| 0.0274        | 32.0    | 240  | 1.1561          | 0.7667   |
| 0.0274        | 32.9333 | 247  | 1.2680          | 0.7833   |
| 0.0251        | 34.0    | 255  | 1.3334          | 0.8      |
| 0.1263        | 34.9333 | 262  | 1.2555          | 0.8167   |
| 0.0389        | 36.0    | 270  | 1.0567          | 0.8      |
| 0.0389        | 36.9333 | 277  | 1.5755          | 0.7667   |
| 0.109         | 38.0    | 285  | 1.5332          | 0.7667   |
| 0.0599        | 38.9333 | 292  | 1.0758          | 0.85     |
| 0.0064        | 40.0    | 300  | 1.1251          | 0.85     |
| 0.0064        | 40.9333 | 307  | 1.3546          | 0.8      |
| 0.003         | 42.0    | 315  | 1.4129          | 0.8      |
| 0.0303        | 42.9333 | 322  | 1.3925          | 0.8      |
| 0.0016        | 44.0    | 330  | 1.3129          | 0.7833   |
| 0.0016        | 44.9333 | 337  | 1.2522          | 0.8      |
| 0.0308        | 46.0    | 345  | 1.3130          | 0.8167   |
| 0.002         | 46.9333 | 352  | 1.3005          | 0.8333   |
| 0.003         | 48.0    | 360  | 1.3434          | 0.8      |
| 0.003         | 48.9333 | 367  | 1.3762          | 0.8      |
| 0.0024        | 50.0    | 375  | 1.4090          | 0.8      |
| 0.0778        | 50.9333 | 382  | 1.3769          | 0.8167   |
| 0.0024        | 52.0    | 390  | 1.3748          | 0.8167   |
| 0.0024        | 52.9333 | 397  | 1.3649          | 0.8167   |
| 0.0132        | 54.0    | 405  | 1.3365          | 0.8167   |
| 0.0102        | 54.9333 | 412  | 1.3363          | 0.8167   |
| 0.0012        | 56.0    | 420  | 1.3374          | 0.8167   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1