---
license: bsd-3-clause
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- accuracy
model-index:
- name: ast-fleurs-langid-dropout-0.2-layers-6
  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. -->

# ast-fleurs-langid-dropout-0.2-layers-6

This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 7.4304
- Accuracy: 0.1802

## 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: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0405        | 1.0   | 16987 | 6.6986          | 0.1722   |
| 0.0002        | 2.0   | 33974 | 7.1284          | 0.1811   |
| 0.0           | 3.0   | 50961 | 7.4304          | 0.1802   |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.2