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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_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: 6.5648576295935746
---
<!-- 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: 0.0743
- Wer: 6.5649
## 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: 450
- training_steps: 4500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2982 | 0.22 | 250 | 0.1790 | 15.9224 |
| 0.1365 | 0.43 | 500 | 0.1313 | 12.7038 |
| 0.1381 | 0.65 | 750 | 0.1126 | 11.4201 |
| 0.1207 | 0.86 | 1000 | 0.1037 | 11.1432 |
| 0.0579 | 1.08 | 1250 | 0.0931 | 9.6404 |
| 0.0665 | 1.3 | 1500 | 0.0929 | 9.4822 |
| 0.0572 | 1.51 | 1750 | 0.0875 | 9.4457 |
| 0.0556 | 1.73 | 2000 | 0.0825 | 8.6122 |
| 0.0458 | 1.94 | 2250 | 0.0778 | 8.2836 |
| 0.0243 | 2.16 | 2500 | 0.0786 | 7.9095 |
| 0.0197 | 2.38 | 2750 | 0.0795 | 7.8578 |
| 0.0229 | 2.59 | 3000 | 0.0758 | 7.4714 |
| 0.0175 | 2.81 | 3250 | 0.0755 | 7.3497 |
| 0.0109 | 3.03 | 3500 | 0.0751 | 7.0759 |
| 0.0098 | 3.24 | 3750 | 0.0773 | 7.1094 |
| 0.0081 | 3.46 | 4000 | 0.0748 | 6.7778 |
| 0.0087 | 3.67 | 4250 | 0.0754 | 6.6774 |
| 0.0086 | 3.89 | 4500 | 0.0743 | 6.5649 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.1
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