|
--- |
|
license: apache-2.0 |
|
base_model: honzapucalek/p6_commonvoice_16_1 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- honzapucalek/p6_hc |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: p6_commonvoice_hc |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: honzapucalek/p6_hc cs |
|
type: honzapucalek/p6_hc |
|
config: cs |
|
split: test |
|
args: cs |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.17960769800148038 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# p6_commonvoice_hc |
|
|
|
This model is a fine-tuned version of [honzapucalek/p6_commonvoice_16_1](https://huggingface.co./honzapucalek/p6_commonvoice_16_1) on the honzapucalek/p6_hc cs dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5960 |
|
- Wer: 0.1796 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 16 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 0.0024 | 14.49 | 1000 | 0.4506 | 0.2335 | |
|
| 0.0024 | 28.99 | 2000 | 0.4568 | 0.1868 | |
|
| 0.0001 | 43.48 | 3000 | 0.5552 | 0.1823 | |
|
| 0.0001 | 57.97 | 4000 | 0.5876 | 0.1807 | |
|
| 0.0001 | 72.46 | 5000 | 0.5960 | 0.1796 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.1 |
|
|
