|
--- |
|
language: |
|
- ymr |
|
license: apache-2.0 |
|
base_model: vasista22/whisper-tamil-small |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: leenag/Malasar_Luke |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# leenag/Malasar_Luke |
|
|
|
This model is a fine-tuned version of [vasista22/whisper-tamil-small](https://huggingface.co./vasista22/whisper-tamil-small) on the Spoken Bible Corpus: Malasar dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5039 |
|
- Wer: 51.9132 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 16 |
|
- 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: 2000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-------:|:----:|:---------------:|:-------:| |
|
| 0.0924 | 11.3636 | 250 | 0.2929 | 52.1416 | |
|
| 0.0013 | 22.7273 | 500 | 0.4152 | 52.8270 | |
|
| 0.0008 | 34.0909 | 750 | 0.4400 | 52.8841 | |
|
| 0.0002 | 45.4545 | 1000 | 0.4761 | 52.1416 | |
|
| 0.0001 | 56.8182 | 1250 | 0.4888 | 51.6276 | |
|
| 0.0001 | 68.1818 | 1500 | 0.4970 | 51.9703 | |
|
| 0.0001 | 79.5455 | 1750 | 0.5021 | 51.7990 | |
|
| 0.0001 | 90.9091 | 2000 | 0.5039 | 51.9132 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.16.0 |
|
- Tokenizers 0.19.1 |
|
|
