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---
language:
- ml
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 Malayalam - Arjun Shaji
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: ml
split: None
args: 'config: ml, split: test'
metrics:
- name: Wer
type: wer
value: 81.60919540229885
---
<!-- 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 Malayalam - Arjun Shaji
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7363
- Wer: 81.6092
## 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: 1000
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| 0.0433 | 18.5185 | 500 | 0.5265 | 94.7126 |
| 0.0144 | 37.0370 | 1000 | 0.5352 | 89.1954 |
| 0.0057 | 55.5556 | 1500 | 0.5989 | 87.5862 |
| 0.0004 | 74.0741 | 2000 | 0.6575 | 82.0690 |
| 0.0 | 92.5926 | 2500 | 0.6616 | 81.6092 |
| 0.0 | 111.1111 | 3000 | 0.6911 | 81.3793 |
| 0.0 | 129.6296 | 3500 | 0.7097 | 81.3793 |
| 0.0 | 148.1481 | 4000 | 0.7232 | 81.3793 |
| 0.0 | 166.6667 | 4500 | 0.7327 | 81.3793 |
| 0.0 | 185.1852 | 5000 | 0.7363 | 81.6092 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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