|
--- |
|
license: apache-2.0 |
|
base_model: openai/whisper-tiny |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: whisper-tiny-khmer-aug-v6 |
|
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. --> |
|
|
|
# whisper-tiny-khmer-aug-v6 |
|
|
|
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2585 |
|
- Wer: 67.4882 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: constant |
|
- lr_scheduler_warmup_steps: 1000 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:| |
|
| 0.7681 | 0.9994 | 837 | 0.3735 | 85.3089 | |
|
| 0.32 | 2.0 | 1675 | 0.2922 | 79.2119 | |
|
| 0.2456 | 2.9994 | 2512 | 0.2541 | 77.7850 | |
|
| 0.2055 | 4.0 | 3350 | 0.2429 | 76.9418 | |
|
| 0.1788 | 4.9994 | 4187 | 0.2487 | 73.0177 | |
|
| 0.1589 | 6.0 | 5025 | 0.2357 | 68.6882 | |
|
| 0.1419 | 6.9994 | 5862 | 0.2396 | 70.0503 | |
|
| 0.1283 | 8.0 | 6700 | 0.2448 | 66.4829 | |
|
| 0.1154 | 8.9994 | 7537 | 0.2484 | 68.8503 | |
|
| 0.1046 | 9.9940 | 8370 | 0.2585 | 67.4882 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.3.1 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
