wav2vec2-xls-r-pt-cv7-from-bp400h
This model is a fine-tuned version of lgris/bp_400h_xlsr2_300M on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.1535
- Wer: 0.1254
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 5000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.4991 | 0.13 | 100 | 0.1774 | 0.1464 |
0.4655 | 0.26 | 200 | 0.1884 | 0.1568 |
0.4689 | 0.39 | 300 | 0.2282 | 0.1672 |
0.4662 | 0.52 | 400 | 0.1997 | 0.1584 |
0.4592 | 0.65 | 500 | 0.1989 | 0.1663 |
0.4533 | 0.78 | 600 | 0.2004 | 0.1698 |
0.4391 | 0.91 | 700 | 0.1888 | 0.1642 |
0.4655 | 1.04 | 800 | 0.1921 | 0.1624 |
0.4138 | 1.17 | 900 | 0.1950 | 0.1602 |
0.374 | 1.3 | 1000 | 0.2077 | 0.1658 |
0.4064 | 1.43 | 1100 | 0.1945 | 0.1596 |
0.3922 | 1.56 | 1200 | 0.2069 | 0.1665 |
0.4226 | 1.69 | 1300 | 0.1962 | 0.1573 |
0.3974 | 1.82 | 1400 | 0.1919 | 0.1553 |
0.3631 | 1.95 | 1500 | 0.1854 | 0.1573 |
0.3797 | 2.08 | 1600 | 0.1902 | 0.1550 |
0.3287 | 2.21 | 1700 | 0.1926 | 0.1598 |
0.3568 | 2.34 | 1800 | 0.1888 | 0.1534 |
0.3415 | 2.47 | 1900 | 0.1834 | 0.1502 |
0.3545 | 2.6 | 2000 | 0.1906 | 0.1560 |
0.3344 | 2.73 | 2100 | 0.1804 | 0.1524 |
0.3308 | 2.86 | 2200 | 0.1741 | 0.1485 |
0.344 | 2.99 | 2300 | 0.1787 | 0.1455 |
0.309 | 3.12 | 2400 | 0.1773 | 0.1448 |
0.312 | 3.25 | 2500 | 0.1738 | 0.1440 |
0.3066 | 3.38 | 2600 | 0.1727 | 0.1417 |
0.2999 | 3.51 | 2700 | 0.1692 | 0.1436 |
0.2985 | 3.64 | 2800 | 0.1732 | 0.1430 |
0.3058 | 3.77 | 2900 | 0.1754 | 0.1402 |
0.2943 | 3.9 | 3000 | 0.1691 | 0.1379 |
0.2813 | 4.03 | 3100 | 0.1754 | 0.1376 |
0.2733 | 4.16 | 3200 | 0.1639 | 0.1363 |
0.2592 | 4.29 | 3300 | 0.1675 | 0.1349 |
0.2697 | 4.42 | 3400 | 0.1618 | 0.1360 |
0.2538 | 4.55 | 3500 | 0.1658 | 0.1348 |
0.2746 | 4.67 | 3600 | 0.1674 | 0.1325 |
0.2655 | 4.8 | 3700 | 0.1655 | 0.1319 |
0.2745 | 4.93 | 3800 | 0.1665 | 0.1316 |
0.2617 | 5.06 | 3900 | 0.1600 | 0.1311 |
0.2674 | 5.19 | 4000 | 0.1623 | 0.1311 |
0.237 | 5.32 | 4100 | 0.1591 | 0.1315 |
0.2669 | 5.45 | 4200 | 0.1584 | 0.1295 |
0.2476 | 5.58 | 4300 | 0.1572 | 0.1285 |
0.2445 | 5.71 | 4400 | 0.1580 | 0.1271 |
0.2207 | 5.84 | 4500 | 0.1567 | 0.1269 |
0.2289 | 5.97 | 4600 | 0.1536 | 0.1260 |
0.2438 | 6.1 | 4700 | 0.1530 | 0.1260 |
0.227 | 6.23 | 4800 | 0.1544 | 0.1249 |
0.2256 | 6.36 | 4900 | 0.1543 | 0.1254 |
0.2184 | 6.49 | 5000 | 0.1535 | 0.1254 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.0
- Tokenizers 0.10.3
- Downloads last month
- 18
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Dataset used to train lgris/wav2vec2-xls-r-pt-cv7-from-bp400h
Evaluation results
- Test WER on Common Voice 7self-reported12.130
- Test CER on Common Voice 7self-reported3.680
- Test WER on Robust Speech Event - Dev Dataself-reported28.230
- Test CER on Robust Speech Event - Dev Dataself-reported12.580
- Test WER on Robust Speech Event - Dev Dataself-reported26.580
- Test WER on Robust Speech Event - Test Dataself-reported26.860