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tags:
- generated_from_trainer
base_model: Lakoc/DeCRED_small_cv_2
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: DeCRED_small_cv_v2_linear_mixing
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. -->
# DeCRED_small_cv_v2_linear_mixing
This model is a fine-tuned version of [Lakoc/DeCRED_small_cv_2](https://huggingface.co/Lakoc/DeCRED_small_cv_2) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9542
- Cer: 0.3765
- Wer: 0.6117
- Mer: 0.5575
- Wil: 0.7685
- Wip: 0.2315
- Hits: 22590
- Substitutions: 20263
- Deletions: 3668
- Insertions: 4527
## 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: 0.0005
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 512
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer | Mer | Wil | Wip | Hits | Substitutions | Deletions | Insertions |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|
| 6.9661 | 0.98 | 22 | 6.8477 | 60.1841 | 50.8357 | 0.9996 | 1.0000 | 0.0000 | 983 | 45533 | 5 | 2319391 |
| 6.5874 | 2.0 | 45 | 6.6100 | 59.9264 | 50.2003 | 0.9995 | 1.0000 | 0.0000 | 1108 | 45404 | 9 | 2289956 |
| 6.4843 | 2.98 | 67 | 6.3899 | 59.4350 | 49.5502 | 0.9995 | 1.0000 | 0.0000 | 1246 | 45261 | 14 | 2259851 |
| 6.1871 | 4.0 | 90 | 6.1667 | 58.7677 | 48.7290 | 0.9994 | 1.0000 | 0.0000 | 1390 | 45122 | 9 | 2221790 |
| 6.1088 | 4.98 | 112 | 5.9594 | 57.9917 | 47.9251 | 0.9993 | 1.0000 | 0.0000 | 1603 | 44900 | 18 | 2184606 |
| 5.8041 | 6.0 | 135 | 5.7487 | 56.6337 | 46.6790 | 0.9992 | 1.0000 | 0.0000 | 1816 | 44680 | 25 | 2126851 |
| 5.7494 | 6.98 | 157 | 5.5529 | 54.6535 | 44.8725 | 0.9991 | 1.0000 | 0.0000 | 1974 | 44513 | 34 | 2042966 |
| 5.4083 | 8.0 | 180 | 5.3546 | 52.4198 | 42.9372 | 0.9989 | 0.9999 | 0.0001 | 2173 | 44298 | 50 | 1953135 |
| 5.3779 | 8.98 | 202 | 5.1706 | 49.7925 | 40.7569 | 0.9988 | 0.9999 | 0.0001 | 2371 | 44091 | 59 | 1851904 |
| 5.02 | 10.0 | 225 | 4.9842 | 46.7020 | 38.1816 | 0.9985 | 0.9999 | 0.0001 | 2603 | 43831 | 87 | 1732326 |
| 4.9776 | 10.98 | 247 | 4.8119 | 43.6679 | 35.8707 | 0.9983 | 0.9999 | 0.0001 | 2852 | 43570 | 99 | 1625071 |
| 4.7425 | 12.0 | 270 | 4.6377 | 39.7527 | 32.6943 | 0.9980 | 0.9999 | 0.0001 | 3054 | 43352 | 115 | 1477503 |
| 4.608 | 12.98 | 292 | 4.4773 | 35.2066 | 29.0084 | 0.9976 | 0.9998 | 0.0002 | 3233 | 43132 | 156 | 1306210 |
| 4.4031 | 14.0 | 315 | 4.3150 | 31.5887 | 26.0092 | 0.9971 | 0.9998 | 0.0002 | 3487 | 42835 | 199 | 1166942 |
| 4.3239 | 14.98 | 337 | 4.1657 | 27.0209 | 22.5064 | 0.9965 | 0.9997 | 0.0003 | 3717 | 42481 | 323 | 1004215 |
| 4.1256 | 16.0 | 360 | 4.0154 | 22.4586 | 18.8399 | 0.9956 | 0.9996 | 0.0004 | 3907 | 42238 | 376 | 833835 |
| 4.0373 | 16.98 | 382 | 3.8773 | 18.2020 | 15.3318 | 0.9942 | 0.9995 | 0.0005 | 4128 | 41849 | 544 | 670857 |
| 3.8293 | 18.0 | 405 | 3.7389 | 14.5637 | 12.3297 | 0.9923 | 0.9993 | 0.0007 | 4442 | 41435 | 644 | 531510 |
| 3.7401 | 18.98 | 427 | 3.6120 | 11.4548 | 9.7572 | 0.9897 | 0.9990 | 0.0010 | 4708 | 41051 | 762 | 412101 |
| 3.5255 | 20.0 | 450 | 3.4851 | 8.4210 | 7.3279 | 0.9852 | 0.9984 | 0.0016 | 5122 | 40427 | 972 | 299500 |
| 3.5611 | 20.98 | 472 | 3.3694 | 5.8830 | 5.3130 | 0.9783 | 0.9974 | 0.0026 | 5473 | 39918 | 1130 | 206120 |
| 3.3464 | 22.0 | 495 | 3.2537 | 4.1319 | 3.8709 | 0.9682 | 0.9959 | 0.0041 | 5905 | 39233 | 1383 | 139463 |
| 3.3134 | 22.98 | 517 | 3.1489 | 3.1610 | 3.0400 | 0.9567 | 0.9940 | 0.0060 | 6408 | 38514 | 1599 | 101309 |
| 3.1154 | 24.0 | 540 | 3.0447 | 2.2506 | 2.2882 | 0.9392 | 0.9909 | 0.0091 | 6887 | 37758 | 1876 | 66816 |
| 3.0684 | 24.98 | 562 | 2.9503 | 1.5946 | 1.7552 | 0.9158 | 0.9861 | 0.0139 | 7503 | 36824 | 2194 | 42636 |
| 2.9926 | 26.0 | 585 | 2.8569 | 1.2290 | 1.4535 | 0.8931 | 0.9808 | 0.0192 | 8097 | 36034 | 2390 | 29195 |
| 2.9429 | 26.98 | 607 | 2.7728 | 1.0860 | 1.3147 | 0.8752 | 0.9757 | 0.0243 | 8722 | 35139 | 2660 | 23363 |
| 2.8033 | 28.0 | 630 | 2.6900 | 0.8996 | 1.1624 | 0.8519 | 0.9687 | 0.0313 | 9399 | 34374 | 2748 | 16952 |
| 2.7652 | 28.98 | 652 | 2.6158 | 0.8134 | 1.0854 | 0.8326 | 0.9615 | 0.0385 | 10155 | 33342 | 3024 | 14126 |
| 2.6598 | 30.0 | 675 | 2.5430 | 0.7254 | 1.0033 | 0.8098 | 0.9526 | 0.0474 | 10964 | 32379 | 3178 | 11116 |
| 2.6088 | 30.98 | 697 | 2.4781 | 0.6766 | 0.9584 | 0.7914 | 0.9439 | 0.0561 | 11755 | 31417 | 3349 | 9819 |
| 2.5442 | 32.0 | 720 | 2.4151 | 0.6563 | 0.9343 | 0.7759 | 0.9354 | 0.0646 | 12556 | 30412 | 3553 | 9501 |
| 2.5035 | 32.98 | 742 | 2.3592 | 0.6205 | 0.8964 | 0.7572 | 0.9252 | 0.0748 | 13370 | 29435 | 3716 | 8552 |
| 2.4259 | 34.0 | 765 | 2.3051 | 0.5803 | 0.8567 | 0.7354 | 0.9123 | 0.0877 | 14341 | 28415 | 3765 | 7674 |
| 2.3946 | 34.98 | 787 | 2.2576 | 0.5549 | 0.8295 | 0.7172 | 0.9004 | 0.0996 | 15216 | 27479 | 3826 | 7282 |
| 2.3014 | 36.0 | 810 | 2.2121 | 0.5257 | 0.8003 | 0.6971 | 0.8864 | 0.1136 | 16180 | 26476 | 3865 | 6888 |
| 2.2883 | 36.98 | 832 | 2.1725 | 0.5050 | 0.7753 | 0.6790 | 0.8733 | 0.1267 | 17049 | 25677 | 3795 | 6598 |
| 2.2694 | 38.0 | 855 | 2.1350 | 0.4803 | 0.7461 | 0.6596 | 0.8587 | 0.1413 | 17913 | 24794 | 3814 | 6102 |
| 2.2372 | 38.98 | 877 | 2.1028 | 0.4635 | 0.7254 | 0.6447 | 0.8465 | 0.1535 | 18597 | 24029 | 3895 | 5821 |
| 2.1639 | 40.0 | 900 | 2.0728 | 0.4458 | 0.7033 | 0.6289 | 0.8335 | 0.1665 | 19309 | 23310 | 3902 | 5508 |
| 2.1478 | 40.98 | 922 | 2.0475 | 0.4303 | 0.6843 | 0.6146 | 0.8211 | 0.1789 | 19960 | 22639 | 3922 | 5271 |
| 2.1546 | 42.0 | 945 | 2.0245 | 0.4172 | 0.6653 | 0.5999 | 0.8083 | 0.1917 | 20644 | 22064 | 3813 | 5075 |
| 2.1382 | 42.98 | 967 | 2.0056 | 0.4062 | 0.6510 | 0.5885 | 0.7979 | 0.2021 | 21179 | 21588 | 3754 | 4942 |
| 2.1007 | 44.0 | 990 | 1.9892 | 0.3961 | 0.6376 | 0.5780 | 0.7881 | 0.2119 | 21656 | 21111 | 3754 | 4798 |
| 2.09 | 44.98 | 1012 | 1.9766 | 0.3885 | 0.6282 | 0.5705 | 0.7810 | 0.2190 | 21996 | 20801 | 3724 | 4698 |
| 2.1065 | 46.0 | 1035 | 1.9664 | 0.3827 | 0.6207 | 0.5644 | 0.7752 | 0.2248 | 22286 | 20556 | 3679 | 4641 |
| 2.1115 | 46.98 | 1057 | 1.9596 | 0.3793 | 0.6157 | 0.5604 | 0.7713 | 0.2287 | 22466 | 20393 | 3662 | 4587 |
| 2.0602 | 48.0 | 1080 | 1.9554 | 0.3770 | 0.6125 | 0.5581 | 0.7691 | 0.2309 | 22564 | 20295 | 3662 | 4537 |
| 1.9657 | 48.89 | 1100 | 1.9542 | 0.3765 | 0.6117 | 0.5575 | 0.7685 | 0.2315 | 22590 | 20263 | 3668 | 4527 |
### Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.0+rocm5.6
- Datasets 2.18.0
- Tokenizers 0.15.2
### Wandb run
https://wandb.ai/butspeechfit/decred_commonvoice_en/runs/DeCRED_small_cv_v2_linear_mixing |