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---
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
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