---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xbgoose/ravdess
metrics:
- accuracy
base_model: ntu-spml/distilhubert
model-index:
- name: distilhubert-finetuned-ravdess
  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. -->

# distilhubert-finetuned-ravdess

This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the RAVDESS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2810
- Accuracy: 0.9236

## 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7599        | 1.0   | 162  | 1.7350          | 0.3264   |
| 1.3271        | 2.0   | 324  | 1.1987          | 0.5972   |
| 0.8845        | 3.0   | 486  | 0.8824          | 0.7639   |
| 0.6083        | 4.0   | 648  | 0.5919          | 0.8403   |
| 0.4952        | 5.0   | 810  | 0.4469          | 0.8611   |
| 0.1386        | 6.0   | 972  | 0.3736          | 0.8681   |
| 0.1028        | 7.0   | 1134 | 0.3645          | 0.8819   |
| 0.053         | 8.0   | 1296 | 0.3079          | 0.9028   |
| 0.0149        | 9.0   | 1458 | 0.2723          | 0.9236   |
| 0.0154        | 10.0  | 1620 | 0.2810          | 0.9236   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.13.0
- Tokenizers 0.13.3