metadata
license: cc0-1.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: ''
results: []
This model is a fine-tuned version of marinone94/xls-r-300m-sv-robust on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.1501
- Wer: 0.1265
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: 0.00025
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.3533 | 1.1 | 100 | 3.2807 | 1.0 |
| 3.1709 | 2.2 | 200 | 3.1325 | 1.0 |
| 3.0573 | 3.3 | 300 | 3.0615 | 1.0 |
| 3.0314 | 4.39 | 400 | 3.0990 | 1.0 |
| 3.0129 | 5.49 | 500 | 3.0400 | 1.0 |
| 2.9964 | 6.59 | 600 | 2.9990 | 1.0 |
| 2.9602 | 7.69 | 700 | 2.9620 | 1.0 |
| 2.8756 | 8.79 | 800 | 2.7302 | 1.0 |
| 2.2931 | 9.89 | 900 | 1.5058 | 0.9776 |
| 1.8427 | 10.98 | 1000 | 0.9155 | 0.7832 |
| 1.4286 | 12.09 | 1100 | 0.4075 | 0.3796 |
| 1.2229 | 13.19 | 1200 | 0.2893 | 0.2652 |
| 1.1106 | 14.28 | 1300 | 0.2469 | 0.2254 |
| 1.0663 | 15.38 | 1400 | 0.2219 | 0.1973 |
| 1.0667 | 16.48 | 1500 | 0.2129 | 0.1894 |
| 1.0193 | 17.58 | 1600 | 0.1991 | 0.1789 |
| 0.9816 | 18.68 | 1700 | 0.1940 | 0.1801 |
| 0.9814 | 19.78 | 1800 | 0.1860 | 0.1667 |
| 0.9787 | 20.87 | 1900 | 0.1888 | 0.1642 |
| 0.9699 | 21.97 | 2000 | 0.1875 | 0.1704 |
| 0.9616 | 23.08 | 2100 | 0.1802 | 0.1617 |
| 0.9378 | 24.17 | 2200 | 0.1793 | 0.1577 |
| 0.888 | 25.27 | 2300 | 0.1764 | 0.1545 |
| 0.8942 | 26.37 | 2400 | 0.1674 | 0.1492 |
| 0.8701 | 27.47 | 2500 | 0.1739 | 0.1512 |
| 0.8555 | 28.57 | 2600 | 0.1690 | 0.1446 |
| 0.8513 | 29.67 | 2700 | 0.1649 | 0.1477 |
| 0.8659 | 30.77 | 2800 | 0.1637 | 0.1422 |
| 0.8419 | 31.86 | 2900 | 0.1614 | 0.1397 |
| 0.8491 | 32.96 | 3000 | 0.1595 | 0.1401 |
| 0.8395 | 34.07 | 3100 | 0.1607 | 0.1376 |
| 0.83 | 35.16 | 3200 | 0.1538 | 0.1379 |
| 0.7835 | 36.26 | 3300 | 0.1602 | 0.1408 |
| 0.7703 | 37.36 | 3400 | 0.1601 | 0.1369 |
| 0.7474 | 38.46 | 3500 | 0.1514 | 0.1342 |
| 0.7719 | 39.56 | 3600 | 0.1593 | 0.1353 |
| 0.7638 | 40.66 | 3700 | 0.1536 | 0.1338 |
| 0.771 | 41.75 | 3800 | 0.1531 | 0.1317 |
| 0.7594 | 42.85 | 3900 | 0.1498 | 0.1288 |
| 0.7383 | 43.95 | 4000 | 0.1527 | 0.1300 |
| 0.7565 | 45.05 | 4100 | 0.1482 | 0.1289 |
| 0.7697 | 46.15 | 4200 | 0.1495 | 0.1272 |
| 0.7194 | 47.25 | 4300 | 0.1493 | 0.1269 |
| 0.7479 | 48.35 | 4400 | 0.1490 | 0.1276 |
| 0.7132 | 49.45 | 4500 | 0.1501 | 0.1265 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0