---
language:
- ro
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- iulik-pisik/audio_vreme
metrics:
- wer
model-index:
- name: Whisper Small Romanian - Vreme
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Vreme ProTv
      type: iulik-pisik/audio_vreme
      config: default
      split: None
      args: 'config: ro, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 7.994245787094123
---

<!-- 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 Romanian - Vreme

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Vreme ProTv dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1873
- Wer: 7.9942

## 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: 16
- 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0141        | 6.02  | 1000 | 0.1417          | 9.2067 |
| 0.0007        | 12.05 | 2000 | 0.1657          | 8.4464 |
| 0.0002        | 18.07 | 3000 | 0.1833          | 8.0353 |
| 0.0001        | 24.1  | 4000 | 0.1873          | 7.9942 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2