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---
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
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