|
--- |
|
language: |
|
- te |
|
license: apache-2.0 |
|
tags: |
|
- whisper-event |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Base Te - Bharat Ramanathan |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: google/fleurs |
|
type: google/fleurs |
|
config: te_in |
|
split: test |
|
metrics: |
|
- type: wer |
|
value: 39.09 |
|
name: WER |
|
--- |
|
|
|
<!-- 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 Base Te - Bharat Ramanathan |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2455 |
|
- Wer: 42.6485 |
|
|
|
## 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: 96 |
|
- eval_batch_size: 64 |
|
- 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: 5000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.6341 | 0.1 | 500 | 0.3894 | 60.7108 | |
|
| 0.349 | 0.2 | 1000 | 0.3081 | 52.0935 | |
|
| 0.2792 | 0.3 | 1500 | 0.2874 | 49.7079 | |
|
| 0.2433 | 0.4 | 2000 | 0.2720 | 47.5657 | |
|
| 0.2224 | 1.06 | 2500 | 0.2632 | 45.2288 | |
|
| 0.2058 | 1.16 | 3000 | 0.2529 | 44.3038 | |
|
| 0.1944 | 1.26 | 3500 | 0.2519 | 44.5959 | |
|
| 0.1869 | 1.36 | 4000 | 0.2475 | 43.7196 | |
|
| 0.1811 | 2.03 | 4500 | 0.2451 | 43.3301 | |
|
| 0.1775 | 2.13 | 5000 | 0.2455 | 42.6485 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.0.dev0 |
|
- Pytorch 1.13.0 |
|
- Datasets 2.7.1.dev0 |
|
- Tokenizers 0.13.2 |
|
|