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---
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: []
---
<!-- 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. -->
# whisper_tiny_fleurs
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
|