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---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- shemo
metrics:
- f1
model-index:
- name: results
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: shemo
type: shemo
config: clean
split: None
args: clean
metrics:
- name: F1
type: f1
value: 0.8335174497965196
---
<!-- 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. -->
# results
This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the shemo dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6161
- F1: 0.8335
## Labels description
- 0 : anger
- 1 : happiness
- 2 : neutral
- 3 : sadness
## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.1127 | 1.0 | 154 | 0.9244 | 0.3968 |
| 0.6982 | 2.0 | 308 | 0.5642 | 0.6435 |
| 0.6246 | 3.0 | 462 | 0.5049 | 0.6273 |
| 0.5097 | 4.0 | 616 | 0.4282 | 0.7246 |
| 0.4496 | 5.0 | 770 | 0.3280 | 0.8158 |
| 0.4476 | 6.0 | 924 | 0.4663 | 0.7978 |
| 0.2212 | 7.0 | 1078 | 0.3253 | 0.8641 |
| 0.1548 | 8.0 | 1232 | 0.9445 | 0.7420 |
| 0.3829 | 9.0 | 1386 | 0.7194 | 0.7880 |
| 0.0773 | 10.0 | 1540 | 0.5301 | 0.8657 |
| 0.2481 | 11.0 | 1694 | 0.5321 | 0.8812 |
| 0.0597 | 12.0 | 1848 | 0.6161 | 0.8335 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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