|
--- |
|
language: |
|
- ta |
|
license: apache-2.0 |
|
base_model: openai/whisper-medium |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- Prajwal-143/ASR-Tamil-cleaned |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper medium ta - Log-Tamil |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: ' asr corpus' |
|
type: Prajwal-143/ASR-Tamil-cleaned |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 10.598921515883243 |
|
--- |
|
|
|
<!-- 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 ta - Log-Tamil |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the asr corpus dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1653 |
|
- Wer Ortho: 37.0213 |
|
- Wer: 10.5989 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: constant_with_warmup |
|
- lr_scheduler_warmup_steps: 50 |
|
- training_steps: 500 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
|
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| |
|
| 0.1591 | 0.0143 | 500 | 0.1653 | 37.0213 | 10.5989 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.3 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
