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---
language:
- es
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
base_model: openai/whisper-small
datasets:
- mozilla-foundation/common_voice_17_0
- google/fleurs
- facebook/multilingual_librispeech
- facebook/voxpopuli
metrics:
- wer
model-index:
- name: Whisper Small Mixed-Spanish
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_17_0 es
type: mozilla-foundation/common_voice_17_0
config: es
split: test
args: es
metrics:
- type: wer
value: 8.634474343167287
name: Wer
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: es_419
split: test
metrics:
- type: wer
value: 5.34
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: facebook/multilingual_librispeech
type: facebook/multilingual_librispeech
config: spanish
split: test
metrics:
- type: wer
value: 6.02
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: facebook/voxpopuli
type: facebook/voxpopuli
config: es
split: test
metrics:
- type: wer
value: 8.55
name: WER
pipeline_tag: automatic-speech-recognition
---
<!-- 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 Mixed-Spanish
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the es datasets:
- mozilla-foundation/common_voice_17_0
- google/fleurs
- facebook/multilingual_librispeech
- facebook/voxpopuli
It achieves the following results on the evaluation set:
- Loss: 0.1809
- Wer: 8.6345
## 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: 64
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.247 | 0.2 | 1000 | 0.2160 | 10.3975 |
| 0.1337 | 0.4 | 2000 | 0.2010 | 9.6749 |
| 0.1401 | 0.6 | 3000 | 0.1905 | 9.0946 |
| 0.1714 | 0.8 | 4000 | 0.1849 | 8.8550 |
| 0.1046 | 1.0 | 5000 | 0.1809 | 8.6345 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |