|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: openai/whisper-small |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Small superU |
|
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 Small superU |
|
|
|
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: 6.3374 |
|
- Wer: 57.2770 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 128 |
|
- total_train_batch_size: 256 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- training_steps: 4000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:| |
|
| 0.0 | 100.0 | 100 | 2.1912 | 59.6244 | |
|
| 0.0 | 200.0 | 200 | 2.3111 | 58.2160 | |
|
| 0.0 | 300.0 | 300 | 2.3886 | 58.2160 | |
|
| 0.0 | 400.0 | 400 | 2.5319 | 60.5634 | |
|
| 0.0 | 500.0 | 500 | 2.7160 | 60.0939 | |
|
| 0.0 | 600.0 | 600 | 2.9609 | 61.0329 | |
|
| 0.0 | 700.0 | 700 | 3.2141 | 61.0329 | |
|
| 0.0 | 800.0 | 800 | 3.4591 | 61.5023 | |
|
| 0.0 | 900.0 | 900 | 3.7213 | 62.4413 | |
|
| 0.0 | 1000.0 | 1000 | 3.9804 | 61.0329 | |
|
| 0.0 | 1100.0 | 1100 | 4.2234 | 78.4038 | |
|
| 0.0 | 1200.0 | 1200 | 4.4138 | 63.3803 | |
|
| 0.0 | 1300.0 | 1300 | 4.5889 | 77.9343 | |
|
| 0.0 | 1400.0 | 1400 | 4.7946 | 70.8920 | |
|
| 0.0 | 1500.0 | 1500 | 4.9337 | 65.7277 | |
|
| 0.0 | 1600.0 | 1600 | 5.0758 | 56.8075 | |
|
| 0.0 | 1700.0 | 1700 | 5.2692 | 56.8075 | |
|
| 0.0 | 1800.0 | 1800 | 5.4087 | 56.8075 | |
|
| 0.0 | 1900.0 | 1900 | 5.5500 | 56.8075 | |
|
| 0.0 | 2000.0 | 2000 | 5.6783 | 56.8075 | |
|
| 0.0 | 2100.0 | 2100 | 5.6287 | 56.8075 | |
|
| 0.0 | 2200.0 | 2200 | 5.6852 | 56.3380 | |
|
| 0.0 | 2300.0 | 2300 | 5.7374 | 56.3380 | |
|
| 0.0 | 2400.0 | 2400 | 5.8023 | 56.3380 | |
|
| 0.0 | 2500.0 | 2500 | 5.8672 | 57.2770 | |
|
| 0.0 | 2600.0 | 2600 | 5.9427 | 57.2770 | |
|
| 0.0 | 2700.0 | 2700 | 5.9891 | 57.2770 | |
|
| 0.0 | 2800.0 | 2800 | 6.0490 | 57.2770 | |
|
| 0.0 | 2900.0 | 2900 | 6.0639 | 57.2770 | |
|
| 0.0 | 3000.0 | 3000 | 6.1095 | 57.2770 | |
|
| 0.0 | 3100.0 | 3100 | 6.1477 | 57.2770 | |
|
| 0.0 | 3200.0 | 3200 | 6.2039 | 57.2770 | |
|
| 0.0 | 3300.0 | 3300 | 6.2346 | 57.2770 | |
|
| 0.0 | 3400.0 | 3400 | 6.2567 | 57.2770 | |
|
| 0.0 | 3500.0 | 3500 | 6.2841 | 57.2770 | |
|
| 0.0 | 3600.0 | 3600 | 6.3028 | 57.2770 | |
|
| 0.0 | 3700.0 | 3700 | 6.3029 | 57.2770 | |
|
| 0.0 | 3800.0 | 3800 | 6.3294 | 57.2770 | |
|
| 0.0 | 3900.0 | 3900 | 6.3346 | 57.2770 | |
|
| 0.0 | 4000.0 | 4000 | 6.3374 | 57.2770 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|