---
language:
- ro
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- VladS159/common_voice_16_1_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 16.1 + Romanian speech synthesis
      type: VladS159/common_voice_16_1_romanian_speech_synthesis
      args: 'config: ro, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 5.588342662448284
---

<!-- 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 16.1 + Romanian speech synthesis dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0795
- Wer: 5.5883

## 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: 10
- eval_batch_size: 10
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 30
- 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: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1485        | 0.43  | 500   | 0.1439          | 14.2157 |
| 0.1344        | 0.86  | 1000  | 0.1165          | 11.6208 |
| 0.0745        | 1.3   | 1500  | 0.0930          | 9.7621  |
| 0.0727        | 1.73  | 2000  | 0.0912          | 9.5309  |
| 0.0269        | 2.16  | 2500  | 0.0802          | 8.1468  |
| 0.0284        | 2.59  | 3000  | 0.0807          | 8.2411  |
| 0.0162        | 3.03  | 3500  | 0.0765          | 7.6691  |
| 0.0123        | 3.46  | 4000  | 0.0782          | 7.2159  |
| 0.0199        | 3.89  | 4500  | 0.0794          | 6.9847  |
| 0.0086        | 4.32  | 5000  | 0.0763          | 6.4766  |
| 0.0083        | 4.75  | 5500  | 0.0768          | 6.6196  |
| 0.0037        | 5.19  | 6000  | 0.0813          | 6.4371  |
| 0.0035        | 5.62  | 6500  | 0.0780          | 6.0203  |
| 0.0025        | 6.05  | 7000  | 0.0826          | 6.4340  |
| 0.0032        | 6.48  | 7500  | 0.0763          | 5.7344  |
| 0.0021        | 6.91  | 8000  | 0.0762          | 5.9260  |
| 0.0011        | 7.35  | 8500  | 0.0790          | 5.5914  |
| 0.001         | 7.78  | 9000  | 0.0788          | 5.5245  |
| 0.0004        | 8.21  | 9500  | 0.0785          | 5.5883  |
| 0.0004        | 8.64  | 10000 | 0.0795          | 5.5883  |


### Framework versions

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