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--- |
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base_model: Lakoc/DeCRED_small_cv_2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: DeCRED_linear_mixing_tuning |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# DeCRED_linear_mixing_tuning |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0590 |
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- Cer: 0.0632 |
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- Wer: 0.1471 |
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- Mer: 0.1444 |
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- Wil: 0.2408 |
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- Wip: 0.7592 |
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- Hits: 23158 |
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- Substitutions: 2931 |
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- Deletions: 484 |
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- Insertions: 494 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.05 |
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- train_batch_size: 256 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 1024 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 50.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Cer | Wer | Mer | Wil | Wip | Hits | Substitutions | Deletions | Insertions | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:| |
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| 1.185 | 2.67 | 20 | 1.1215 | 0.0646 | 0.1520 | 0.1492 | 0.2479 | 0.7521 | 23030 | 3013 | 530 | 496 | |
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| 1.0639 | 5.33 | 40 | 1.0717 | 0.0634 | 0.1480 | 0.1453 | 0.2420 | 0.7580 | 23124 | 2939 | 510 | 483 | |
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| 1.0957 | 8.0 | 60 | 1.0612 | 0.0628 | 0.1464 | 0.1438 | 0.2402 | 0.7598 | 23162 | 2929 | 482 | 480 | |
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| 1.0936 | 10.67 | 80 | 1.0595 | 0.0631 | 0.1469 | 0.1442 | 0.2407 | 0.7593 | 23158 | 2934 | 481 | 488 | |
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| 1.0804 | 13.33 | 100 | 1.0591 | 0.0630 | 0.1468 | 0.1441 | 0.2405 | 0.7595 | 23164 | 2929 | 480 | 492 | |
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| 1.1044 | 16.0 | 120 | 1.0591 | 0.0631 | 0.1469 | 0.1442 | 0.2405 | 0.7595 | 23162 | 2929 | 482 | 492 | |
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| 1.0836 | 18.67 | 140 | 1.0589 | 0.0631 | 0.1468 | 0.1442 | 0.2405 | 0.7595 | 23163 | 2929 | 481 | 492 | |
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| 1.0924 | 21.33 | 160 | 1.0590 | 0.0632 | 0.1471 | 0.1444 | 0.2408 | 0.7592 | 23158 | 2931 | 484 | 494 | |
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| 1.1048 | 24.0 | 180 | 1.0590 | 0.0632 | 0.1471 | 0.1444 | 0.2408 | 0.7592 | 23158 | 2931 | 484 | 494 | |
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| 1.0858 | 26.67 | 200 | 1.0589 | 0.0631 | 0.1470 | 0.1443 | 0.2407 | 0.7593 | 23160 | 2929 | 484 | 494 | |
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| 1.0953 | 29.33 | 220 | 1.0589 | 0.0631 | 0.1468 | 0.1442 | 0.2405 | 0.7595 | 23163 | 2929 | 481 | 492 | |
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| 1.1308 | 32.0 | 240 | 1.0590 | 0.0632 | 0.1471 | 0.1444 | 0.2408 | 0.7592 | 23158 | 2931 | 484 | 494 | |
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### Framework versions |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.2.0+rocm5.6 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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