metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: XLS-R_Synthesis_ALL_v2
results: []
XLS-R_Synthesis_ALL_v2
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1577
- Wer: 0.1671
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: 18
- eval_batch_size: 9
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 72
- total_eval_batch_size: 18
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.5648 | 1.0 | 2611 | 1.3992 | 0.9921 |
| 0.7741 | 2.0 | 5223 | 0.3761 | 0.4506 |
| 0.431 | 3.0 | 7834 | 0.2574 | 0.3203 |
| 0.3323 | 4.0 | 10446 | 0.2205 | 0.2609 |
| 0.2818 | 5.0 | 13057 | 0.2050 | 0.2260 |
| 0.2514 | 6.0 | 15669 | 0.1896 | 0.2105 |
| 0.2318 | 7.0 | 18280 | 0.1766 | 0.2024 |
| 0.2189 | 8.0 | 20892 | 0.1736 | 0.1968 |
| 0.2098 | 9.0 | 23503 | 0.1755 | 0.1917 |
| 0.2024 | 10.0 | 26115 | 0.1707 | 0.1931 |
| 0.1966 | 11.0 | 28726 | 0.1636 | 0.1871 |
| 0.1893 | 12.0 | 31338 | 0.1719 | 0.1839 |
| 0.1808 | 13.0 | 33949 | 0.1684 | 0.1815 |
| 0.1756 | 14.0 | 36561 | 0.1631 | 0.1768 |
| 0.1702 | 15.0 | 39172 | 0.1670 | 0.1757 |
| 0.1651 | 16.0 | 41784 | 0.1627 | 0.1718 |
| 0.1596 | 17.0 | 44395 | 0.1572 | 0.1683 |
| 0.1553 | 18.0 | 47007 | 0.1614 | 0.1675 |
| 0.1528 | 19.0 | 49618 | 0.1701 | 0.1723 |
| 0.1502 | 20.0 | 52230 | 0.1598 | 0.1654 |
| 0.1839 | 21.0 | 54841 | 0.2059 | 0.2144 |
| 0.2445 | 22.0 | 57453 | 0.2215 | 0.2463 |
| 0.2002 | 23.0 | 60064 | 0.1703 | 0.1788 |
| 0.1534 | 24.0 | 62676 | 0.1634 | 0.1698 |
| 0.1449 | 25.0 | 65287 | 0.1577 | 0.1671 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0