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---
library_name: transformers
language:
- ta
license: apache-2.0
base_model: Singhamarjeet8130/whisper-medium-hi
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Medium Hi ta - Amarjeet
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 13.0
type: mozilla-foundation/common_voice_13_0
config: ta
split: test
args: 'config: ta, split: test'
metrics:
- name: Wer
type: wer
value: 37.38483391323612
---
<!-- 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 Medium Hi ta - Amarjeet
This model is a fine-tuned version of [Singhamarjeet8130/whisper-medium-hi](https://huggingface.co/Singhamarjeet8130/whisper-medium-hi) on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1794
- Wer: 37.3848
## 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: Use 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.133 | 0.2894 | 1000 | 0.2347 | 45.2937 |
| 0.1146 | 0.5787 | 2000 | 0.2040 | 41.4025 |
| 0.099 | 0.8681 | 3000 | 0.1835 | 38.8261 |
| 0.0652 | 1.1574 | 4000 | 0.1794 | 37.3848 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0
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