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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 - 3 gpus
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: 6.359842831470257
---
<!-- 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 - 3 gpus
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: 0.0878
- Wer: 6.3598
## 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: 5e-06
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2346 | 0.42 | 500 | 0.1671 | 15.7382 |
| 0.1441 | 0.85 | 1000 | 0.1183 | 12.1318 |
| 0.0887 | 1.27 | 1500 | 0.1026 | 10.3012 |
| 0.0821 | 1.7 | 2000 | 0.0926 | 9.8230 |
| 0.0403 | 2.12 | 2500 | 0.0871 | 9.1590 |
| 0.0394 | 2.55 | 3000 | 0.0914 | 8.8788 |
| 0.0381 | 2.97 | 3500 | 0.0790 | 8.2909 |
| 0.0178 | 3.4 | 4000 | 0.0825 | 7.7579 |
| 0.0185 | 3.82 | 4500 | 0.0776 | 7.4929 |
| 0.0102 | 4.25 | 5000 | 0.0818 | 7.4350 |
| 0.0105 | 4.67 | 5500 | 0.0803 | 6.9599 |
| 0.0054 | 5.1 | 6000 | 0.0830 | 6.9264 |
| 0.0046 | 5.52 | 6500 | 0.0827 | 6.6949 |
| 0.005 | 5.95 | 7000 | 0.0831 | 6.7101 |
| 0.0043 | 6.37 | 7500 | 0.0840 | 6.6462 |
| 0.003 | 6.8 | 8000 | 0.0845 | 6.5274 |
| 0.0017 | 7.22 | 8500 | 0.0875 | 6.5121 |
| 0.0015 | 7.65 | 9000 | 0.0867 | 6.4025 |
| 0.0012 | 8.07 | 9500 | 0.0875 | 6.3568 |
| 0.001 | 8.5 | 10000 | 0.0878 | 6.3598 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.1
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