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---
language:
- sr
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Serbian - Drishti Sharma
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: sr
split: test
args: sr
metrics:
- name: Wer
type: wer
value: 11.614730878186968
---
<!-- 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 Serbian - Drishti Sharma
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3873
- Wer: 11.6147
## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 800
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1691 | 1.89 | 100 | 0.2398 | 13.5977 |
| 0.0571 | 3.77 | 200 | 0.2419 | 12.7479 |
| 0.0225 | 5.66 | 300 | 0.2869 | 12.2218 |
| 0.0108 | 7.55 | 400 | 0.3085 | 12.2622 |
| 0.0121 | 9.43 | 500 | 0.3478 | 11.6147 |
| 0.0015 | 11.32 | 600 | 0.3702 | 11.5338 |
| 0.0005 | 13.21 | 700 | 0.3839 | 11.6147 |
| 0.0005 | 15.09 | 800 | 0.3873 | 11.6147 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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