|
--- |
|
license: apache-2.0 |
|
base_model: facebook/hubert-large-ls960-ft |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: hubert-large-ls960-ft-V2-10 |
|
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. --> |
|
|
|
# hubert-large-ls960-ft-V2-10 |
|
|
|
This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4727 |
|
- Wer: 0.0628 |
|
- Per: 0.0490 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Per | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 14.6873 | 1.0 | 164 | 3.2286 | 1.0 | 1.0 | |
|
| 3.2356 | 2.0 | 328 | 3.1024 | 1.0 | 1.0 | |
|
| 2.6803 | 3.0 | 492 | 1.9833 | 0.9224 | 0.9382 | |
|
| 1.5141 | 4.0 | 656 | 1.1059 | 0.4099 | 0.3923 | |
|
| 0.7862 | 5.0 | 820 | 0.6129 | 0.1587 | 0.1357 | |
|
| 0.4004 | 6.0 | 984 | 0.4939 | 0.0939 | 0.0748 | |
|
| 0.2791 | 7.0 | 1148 | 0.4888 | 0.0815 | 0.0646 | |
|
| 0.2168 | 8.0 | 1312 | 0.5083 | 0.0830 | 0.0662 | |
|
| 0.1726 | 9.0 | 1476 | 0.4748 | 0.0749 | 0.0596 | |
|
| 0.1412 | 10.0 | 1640 | 0.4955 | 0.0742 | 0.0575 | |
|
| 0.1156 | 11.0 | 1804 | 0.4986 | 0.0715 | 0.0564 | |
|
| 0.1321 | 12.0 | 1968 | 0.5101 | 0.0703 | 0.0552 | |
|
| 0.103 | 13.0 | 2132 | 0.4728 | 0.0668 | 0.0527 | |
|
| 0.0772 | 14.0 | 2296 | 0.4832 | 0.0649 | 0.0509 | |
|
| 0.0858 | 15.0 | 2460 | 0.4830 | 0.0649 | 0.0505 | |
|
| 0.0874 | 16.0 | 2624 | 0.4697 | 0.0642 | 0.0509 | |
|
| 0.0784 | 17.0 | 2788 | 0.4499 | 0.0652 | 0.0516 | |
|
| 0.0703 | 18.0 | 2952 | 0.4699 | 0.0638 | 0.0500 | |
|
| 0.062 | 19.0 | 3116 | 0.4757 | 0.0634 | 0.0496 | |
|
| 0.0588 | 20.0 | 3280 | 0.4727 | 0.0628 | 0.0490 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
|
|