|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper-Timit-fineT-16 |
|
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-Timit-fineT-16 |
|
|
|
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: 0.1388 |
|
- Wer: 38.9999 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 8 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.0356 | 1.73 | 500 | 0.0982 | 61.5030 | |
|
| 0.0022 | 3.46 | 1000 | 0.1059 | 80.2039 | |
|
| 0.0018 | 5.19 | 1500 | 0.1167 | 47.5479 | |
|
| 0.0002 | 6.92 | 2000 | 0.1204 | 49.5247 | |
|
| 0.0002 | 8.65 | 2500 | 0.1280 | 51.4465 | |
|
| 0.0001 | 10.38 | 3000 | 0.1316 | 44.9029 | |
|
| 0.0001 | 12.11 | 3500 | 0.1345 | 42.7538 | |
|
| 0.0001 | 13.84 | 4000 | 0.1368 | 40.0744 | |
|
| 0.0001 | 15.57 | 4500 | 0.1382 | 40.0813 | |
|
| 0.0001 | 17.3 | 5000 | 0.1388 | 38.9999 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.28.0.dev0 |
|
- Pytorch 1.13.0 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.13.2 |
|
|
