---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 3_epoch_noFirVox
  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. -->

# 3_epoch_noFirVox

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the /home/investigacion/disco4TB/workspace_pablo/firvox_whisper_research/finetunnig/dataset/dataset_parquet/dataset_1000x6_noFirVox_correctedpaths.parquet dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4373
- Accuracy: 0.87

## 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: 16
- eval_batch_size: 32
- seed: 0
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9061        | 1.0   | 80   | 0.7686          | 0.7856   |
| 0.4682        | 2.0   | 160  | 0.5186          | 0.8389   |
| 0.286         | 3.0   | 240  | 0.4373          | 0.87     |


### Framework versions

- Transformers 4.44.1
- Pytorch 1.11.0
- Datasets 2.19.1
- Tokenizers 0.19.1