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---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: BANG - v1
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Radio-Modified Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: hi
split: test
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 3.2167950562939134
---
<!-- 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. -->
# BANG - v1
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the Radio-Modified Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0031
- Wer: 3.2168
## 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: 16
- 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.2164 | 5.0237 | 1000 | 0.1425 | 23.3895 |
| 0.0328 | 11.0023 | 2000 | 0.0373 | 9.2948 |
| 0.0134 | 16.026 | 3000 | 0.0078 | 5.3966 |
| 0.0021 | 22.0045 | 4000 | 0.0031 | 3.2168 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|