|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: xls-r_cv_ur |
|
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. --> |
|
|
|
# xls-r_cv_ur |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5811 |
|
- Wer: 1.0 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 100 |
|
- num_epochs: 20 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:---:| |
|
| 8.2414 | 1.14 | 100 | 2.2232 | 1.0 | |
|
| 1.9235 | 2.27 | 200 | 1.8280 | 1.0 | |
|
| 1.8174 | 3.41 | 300 | 1.8247 | 1.0 | |
|
| 1.8305 | 4.55 | 400 | 1.7873 | 1.0 | |
|
| 1.7604 | 5.68 | 500 | 1.7839 | 1.0 | |
|
| 1.7727 | 6.82 | 600 | 1.7499 | 1.0 | |
|
| 1.7474 | 7.95 | 700 | 1.7209 | 1.0 | |
|
| 1.7105 | 9.09 | 800 | 1.6658 | 1.0 | |
|
| 1.6932 | 10.23 | 900 | 1.5940 | 1.0 | |
|
| 1.6064 | 11.36 | 1000 | 1.4630 | 1.0 | |
|
| 1.4748 | 12.5 | 1100 | 1.1940 | 1.0 | |
|
| 1.2831 | 13.64 | 1200 | 0.9712 | 1.0 | |
|
| 1.1637 | 14.77 | 1300 | 0.8227 | 1.0 | |
|
| 1.0745 | 15.91 | 1400 | 0.7349 | 1.0 | |
|
| 0.9797 | 17.05 | 1500 | 0.6512 | 1.0 | |
|
| 0.9098 | 18.18 | 1600 | 0.6124 | 1.0 | |
|
| 0.8953 | 19.32 | 1700 | 0.5811 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.0 |
|
- Pytorch 1.11.0+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
