|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-large-xlsr-53 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-large-xlsr-faroese-100h-30k-steps |
|
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. --> |
|
|
|
# wav2vec2-large-xlsr-faroese-100h-30k-steps |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1354 |
|
- Wer: 25.2668 |
|
|
|
## 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: 0.0003 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- training_steps: 30000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-------:|:-----:|:---------------:|:-------:| |
|
| 0.6576 | 0.4640 | 1000 | 0.4914 | 63.2323 | |
|
| 0.4625 | 0.9281 | 2000 | 0.3354 | 47.7149 | |
|
| 0.3475 | 1.3921 | 3000 | 0.2567 | 41.2321 | |
|
| 0.2979 | 1.8561 | 4000 | 0.2330 | 38.5595 | |
|
| 0.235 | 2.3202 | 5000 | 0.2173 | 37.0143 | |
|
| 0.2737 | 2.7842 | 6000 | 0.2089 | 35.6704 | |
|
| 0.2095 | 3.2483 | 7000 | 0.1939 | 33.8484 | |
|
| 0.1916 | 3.7123 | 8000 | 0.1836 | 33.3904 | |
|
| 0.176 | 4.1763 | 9000 | 0.1794 | 31.9609 | |
|
| 0.1609 | 4.6404 | 10000 | 0.1709 | 31.3771 | |
|
| 0.1941 | 5.1044 | 11000 | 0.1693 | 30.9392 | |
|
| 0.1517 | 5.5684 | 12000 | 0.1693 | 30.9493 | |
|
| 0.1583 | 6.0325 | 13000 | 0.1532 | 29.6859 | |
|
| 0.14 | 6.4965 | 14000 | 0.1604 | 29.3185 | |
|
| 0.1688 | 6.9606 | 15000 | 0.1488 | 29.4041 | |
|
| 0.1553 | 7.4246 | 16000 | 0.1607 | 28.6893 | |
|
| 0.1483 | 7.8886 | 17000 | 0.1526 | 28.0552 | |
|
| 0.1442 | 8.3527 | 18000 | 0.1537 | 28.2615 | |
|
| 0.1304 | 8.8167 | 19000 | 0.1497 | 27.5569 | |
|
| 0.1104 | 9.2807 | 20000 | 0.1622 | 27.5871 | |
|
| 0.1225 | 9.7448 | 21000 | 0.1493 | 26.8724 | |
|
| 0.1014 | 10.2088 | 22000 | 0.1433 | 26.7516 | |
|
| 0.1087 | 10.6729 | 23000 | 0.1365 | 26.2130 | |
|
| 0.0855 | 11.1369 | 24000 | 0.1421 | 26.2432 | |
|
| 0.0865 | 11.6009 | 25000 | 0.1339 | 25.9714 | |
|
| 0.0603 | 12.0650 | 26000 | 0.1364 | 25.6694 | |
|
| 0.0663 | 12.5290 | 27000 | 0.1362 | 25.3876 | |
|
| 0.0648 | 12.9930 | 28000 | 0.1358 | 25.4681 | |
|
| 0.0638 | 13.4571 | 29000 | 0.1366 | 25.3423 | |
|
| 0.0629 | 13.9211 | 30000 | 0.1354 | 25.2668 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.1+cu121 |
|
- Datasets 3.0.0 |
|
- Tokenizers 0.19.1 |
|
|
