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---
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 Russian (Trained with Spanish accent)
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: 16.29353233830846
---
<!-- 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 Russian (Trained with Spanish accent)
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Spanish English dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2750
- Wer: 16.2935
## 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 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: 1500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.4622 | 0.4864 | 500 | 0.3288 | 17.9851 |
| 0.2832 | 0.9728 | 1000 | 0.2934 | 17.0896 |
| 0.1902 | 1.4591 | 1500 | 0.2750 | 16.2935 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1
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