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---
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small Tr - CV 43h large batch
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.1
type: mozilla-foundation/common_voice_16_1
config: tr
split: None
args: 'config: tr, split: test'
metrics:
- name: Wer
type: wer
value: 21.060292928385298
---
<!-- 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 Small Tr - CV 43h large batch
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2890
- Wer: 21.0603
## 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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.192 | 0.73 | 500 | 0.2638 | 22.1026 |
| 0.1238 | 1.46 | 1000 | 0.2492 | 21.2921 |
| 0.0663 | 2.19 | 1500 | 0.2483 | 20.7799 |
| 0.0656 | 2.92 | 2000 | 0.2445 | 20.3073 |
| 0.0391 | 3.65 | 2500 | 0.2575 | 21.1466 |
| 0.0203 | 4.38 | 3000 | 0.2744 | 20.9956 |
| 0.0125 | 5.11 | 3500 | 0.2841 | 20.9597 |
| 0.0096 | 5.84 | 4000 | 0.2890 | 21.0603 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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