|
--- |
|
language: |
|
- ka |
|
license: apache-2.0 |
|
tags: |
|
- whisper-event |
|
- generated_from_trainer |
|
datasets: |
|
- google/fleurs |
|
model-index: |
|
- name: whisper-small-tamil |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: google/fleurs |
|
config: ta_in |
|
split: test |
|
type: google/fleurs |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 23.1257 |
|
--- |
|
|
|
<!-- 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-tamil |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset for Kannada. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2507 |
|
- Wer: 23.1257 |
|
## 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 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- training_steps: 5000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.0792 | 2.27 | 500 | 0.2674 | 24.7048 | |
|
| 0.0067 | 12.19 | 1000 | 0.1930 | 23.7758 | |
|
| 0.0011 | 18.29 | 1500 | 0.2161 | 23.3225 | |
|
| 0.0002 | 24.39 | 2000 | 0.2294 | 23.1332 | |
|
| 0.0001 | 30.48 | 2500 | 0.2406 | 23.1652 | |
|
| 0.0001 | 36.58 | 3000 | 0.2461 | 23.1531 | |
|
| 0.0001 | 42.68 | 3500 | 0.2493 | 23.1108 | |
|
| 0.0001 | 48.78 | 4000 | 0.2507 | 23.1257 | |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.24.0 |
|
- Pytorch 1.13.0+cu117 |
|
- Datasets 2.7.1 |
|
- Tokenizers 0.13.2 |
|
|
