metadata

library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - audio-classification
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: whisper_tiny_fleurs
    results: []

whisper_tiny_fleurs

This model is a fine-tuned version of 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: 0.9658
Accuracy: 0.7744

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: 1.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0287	1.0	80	0.9658	0.7744

Framework versions

Transformers 4.44.1
Pytorch 1.11.0
Datasets 2.19.1
Tokenizers 0.19.1