---
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