|
---
|
|
license: apache-2.0
|
|
base_model: openai/whisper-small.en
|
|
tags:
|
|
- generated_from_trainer
|
|
metrics:
|
|
- wer
|
|
model-index:
|
|
- name: abbenedekwhisper-small.en-finetuning2-D3K
|
|
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. -->
|
|
|
|
# abbenedekwhisper-small.en-finetuning2-D3K
|
|
|
|
This model is a fine-tuned version of [openai/whisper-small.en](https://huggingface.co/openai/whisper-small.en) on the None dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 7.0682
|
|
- Cer: 53.2554
|
|
- Wer: 135.0993
|
|
- Ser: 100.0
|
|
- Cer Clean: 0.5008
|
|
- Wer Clean: 0.6623
|
|
- Ser Clean: 1.7544
|
|
|
|
## 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-08
|
|
- train_batch_size: 16
|
|
- 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: 5
|
|
- training_steps: 50
|
|
- mixed_precision_training: Native AMP
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer | Ser | Cer Clean | Wer Clean | Ser Clean |
|
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:--------:|:-----:|:---------:|:---------:|:---------:|
|
|
| 7.4342 | 0.05 | 10 | 7.0727 | 53.2554 | 135.0993 | 100.0 | 0.5008 | 0.6623 | 1.7544 |
|
|
| 7.2902 | 0.11 | 20 | 7.0722 | 53.2554 | 135.0993 | 100.0 | 0.5008 | 0.6623 | 1.7544 |
|
|
| 6.9726 | 0.16 | 30 | 7.0711 | 53.2554 | 135.0993 | 100.0 | 0.5008 | 0.6623 | 1.7544 |
|
|
| 7.3598 | 0.21 | 40 | 7.0705 | 53.2554 | 135.0993 | 100.0 | 0.5008 | 0.6623 | 1.7544 |
|
|
| 7.0578 | 0.27 | 50 | 7.0682 | 53.2554 | 135.0993 | 100.0 | 0.5008 | 0.6623 | 1.7544 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.39.3
|
|
- Pytorch 2.2.2+cu121
|
|
- Datasets 2.14.5
|
|
- Tokenizers 0.15.2
|
|
|
