metadata
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- Spanish_english
metrics:
- wer
model-index:
- name: Whisper tiny Spanish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Spanish English
type: Spanish_english
args: 'config: default, split: test'
metrics:
- name: Wer
type: wer
value: 81.5477909327173
Whisper tiny Spanish
This model is a fine-tuned version of openai/whisper-tiny on the Spanish English dataset. It achieves the following results on the evaluation set:
- Loss: 1.6335
- Wer: 81.5478
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: 2
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6927 | 3.6630 | 1000 | 1.6329 | 77.3607 |
| 0.1502 | 7.3260 | 2000 | 1.6335 | 81.5478 |
Framework versions
- Transformers 4.57.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.2.0
- Tokenizers 0.22.1