transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ro dataset:VladS159/common_voice_romanian_speech_synthesis base_model:openai/whisper-medium license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- ro
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- VladS159/common_voice_romanian_speech_synthesis
metrics:
- wer
model-index:
- name: Whisper Medium Ro - Sarbu Vlad - multi gpu
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.1 + Romanian speech synthesis
      type: VladS159/common_voice_romanian_speech_synthesis
      args: 'config: ro, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 8.350571915307862
---

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# Whisper Medium Ro - Sarbu Vlad - multi gpu

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: 0.0807
- Wer: 8.3506

## 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: 200
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1753        | 0.22  | 250  | 0.1553          | 14.6629 |
| 0.1227        | 0.43  | 500  | 0.1203          | 11.8855 |
| 0.1286        | 0.65  | 750  | 0.1053          | 10.8999 |
| 0.1129        | 0.86  | 1000 | 0.0969          | 10.4557 |
| 0.051         | 1.08  | 1250 | 0.0882          | 9.1050  |
| 0.0589        | 1.3   | 1500 | 0.0851          | 9.0138  |
| 0.05          | 1.51  | 1750 | 0.0832          | 8.7795  |
| 0.0492        | 1.73  | 2000 | 0.0807          | 8.3506  |


### Framework versions

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