---
language:
- ro
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- VladS159/common_voice_17_0_romanian_speech_synthesis
metrics:
- wer
model-index:
- name: Whisper Medium Ro - Sarbu Vlad - multi gpu --> 3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0 + Romanian speech synthesis
      type: VladS159/common_voice_17_0_romanian_speech_synthesis
      args: 'config: ro, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 5.7841674027595875
---

<!-- 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 Medium Ro - Sarbu Vlad - multi gpu --> 3

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 + Romanian speech synthesis dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0777
- Wer: 5.7842

## 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: 11
- eval_batch_size: 10
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 33
- total_eval_batch_size: 30
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1807        | 0.47  | 500  | 0.1359          | 13.4050 |
| 0.1066        | 0.93  | 1000 | 0.1097          | 11.4191 |
| 0.0707        | 1.4   | 1500 | 0.0948          | 10.0972 |
| 0.0649        | 1.87  | 2000 | 0.0824          | 8.7874  |
| 0.0249        | 2.34  | 2500 | 0.0828          | 8.6930  |
| 0.0275        | 2.8   | 3000 | 0.0792          | 7.8402  |
| 0.0139        | 3.27  | 3500 | 0.0748          | 6.7619  |
| 0.0121        | 3.74  | 4000 | 0.0766          | 7.2492  |
| 0.0071        | 4.21  | 4500 | 0.0759          | 6.5335  |
| 0.005         | 4.67  | 5000 | 0.0764          | 6.3903  |
| 0.0036        | 5.14  | 5500 | 0.0768          | 6.0217  |
| 0.0037        | 5.61  | 6000 | 0.0770          | 6.1009  |
| 0.0013        | 6.07  | 6500 | 0.0768          | 5.9182  |
| 0.0012        | 6.54  | 7000 | 0.0765          | 5.7933  |
| 0.0014        | 7.01  | 7500 | 0.0770          | 5.8299  |
| 0.0008        | 7.48  | 8000 | 0.0777          | 5.7842  |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.1