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library_name: transformers
language:
- ta
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper tiny ta - Sanchit Gandhi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: ta
split: None
args: 'config: ta, split: test'
metrics:
- name: Wer
type: wer
value: 81.81818181818183
---
<!-- 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 tiny ta - Sanchit Gandhi
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1323
- Wer: 81.8182
- Cer: 25.8981
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|
| 0.3684 | 1.5873 | 100 | 0.7662 | 96.3317 | 49.9906 |
| 0.1868 | 3.1746 | 200 | 0.8380 | 86.7624 | 29.6596 |
| 0.097 | 4.7619 | 300 | 0.9112 | 85.0080 | 29.5091 |
| 0.0481 | 6.3492 | 400 | 0.9833 | 85.4864 | 29.9041 |
| 0.0332 | 7.9365 | 500 | 0.9751 | 83.0941 | 30.1862 |
| 0.0154 | 9.5238 | 600 | 1.0561 | 85.4864 | 29.2082 |
| 0.0064 | 11.1111 | 700 | 1.1354 | 83.5726 | 27.3462 |
| 0.003 | 12.6984 | 800 | 1.1157 | 83.7321 | 27.1958 |
| 0.0006 | 14.2857 | 900 | 1.1344 | 82.7751 | 26.4435 |
| 0.0004 | 15.8730 | 1000 | 1.1323 | 81.8182 | 25.8981 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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