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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- atulksingh/mypin-voice-dataset
metrics:
- wer
model-index:
- name: Whisper Base myPin
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Domain Based voice
type: atulksingh/mypin-voice-dataset
config: default
split: None
args: 'split: test'
metrics:
- name: Wer
type: wer
value: 3.9215686274509802
---
<!-- 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 Base myPin
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Domain Based voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0078
- Wer: 3.9216
## 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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0007 | 100.0 | 500 | 0.0086 | 3.9216 |
| 0.0003 | 200.0 | 1000 | 0.0079 | 3.9216 |
| 0.0002 | 300.0 | 1500 | 0.0078 | 3.9216 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
|