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---
language:
- eng
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small eng - Himanshu
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: NPTEL Sample dataset
type: mozilla-foundation/common_voice_11_0
args: 'config: eng, split: test'
metrics:
- name: Wer
type: wer
value: 17.920937042459737
---
<!-- 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 eng - Himanshu
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the NPTEL Sample dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5925
- Wer: 17.9209
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0014 | 20.0 | 1000 | 0.5083 | 17.6574 |
| 0.0008 | 40.0 | 2000 | 0.5600 | 18.1552 |
| 0.0002 | 60.0 | 3000 | 0.5837 | 17.8917 |
| 0.0002 | 80.0 | 4000 | 0.5925 | 17.9209 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|