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---
language:
- es
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- Drazcat/Cencosud
metrics:
- wer
model-index:
- name: Whisper Small Es - GoCloud
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: 30seg
type: Drazcat/Cencosud
args: 'config: es, split: test'
metrics:
- name: Wer
type: wer
value: 0.0
---
<!-- 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 Small Es - GoCloud
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the 30seg dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0028
- Wer: 0.0
## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 25
- training_steps: 200
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2944 | 5.56 | 50 | 0.1392 | 79.6117 |
| 0.08 | 11.11 | 100 | 0.0569 | 46.0472 |
| 0.0204 | 16.67 | 150 | 0.0086 | 0.0 |
| 0.0028 | 22.22 | 200 | 0.0028 | 0.0 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
|