---
license: bsd-3-clause
base_model: minoosh/ast-finetuned-audioset-10-10-0.4593-finetuned-ie
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ASTie-finetuned-on-shEMO_speech
  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. -->

# ASTie-finetuned-on-shEMO_speech

This model is a fine-tuned version of [minoosh/ast-finetuned-audioset-10-10-0.4593-finetuned-ie](https://huggingface.co/minoosh/ast-finetuned-audioset-10-10-0.4593-finetuned-ie) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1646
- Accuracy: 0.81

## 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: 3e-05
- 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: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8071        | 1.0   | 75   | 0.7501          | 0.7933   |
| 0.6495        | 2.0   | 150  | 0.6482          | 0.78     |
| 0.2065        | 3.0   | 225  | 0.6468          | 0.82     |
| 0.0629        | 4.0   | 300  | 0.8847          | 0.78     |
| 0.014         | 5.0   | 375  | 0.9425          | 0.81     |
| 0.0086        | 6.0   | 450  | 0.8603          | 0.83     |
| 0.0017        | 7.0   | 525  | 0.9790          | 0.8367   |
| 0.0005        | 8.0   | 600  | 0.9910          | 0.8267   |
| 0.0002        | 9.0   | 675  | 0.9920          | 0.8433   |
| 0.0067        | 10.0  | 750  | 1.0013          | 0.84     |
| 0.0001        | 11.0  | 825  | 1.0186          | 0.8433   |
| 0.0001        | 12.0  | 900  | 1.0189          | 0.8433   |
| 0.0001        | 13.0  | 975  | 1.0227          | 0.8433   |
| 0.0038        | 14.0  | 1050 | 1.0279          | 0.8433   |
| 0.0034        | 15.0  | 1125 | 1.0293          | 0.8433   |


### Framework versions

- Transformers 4.34.1
- Pytorch 1.12.0+cu116
- Datasets 2.14.6
- Tokenizers 0.14.1