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--- |
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license: apache-2.0 |
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base_model: google/byt5-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: byt5-base-indocollex-informal-to-formal-wordformation |
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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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# byt5-base-indocollex-informal-to-formal-wordformation |
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This model is a fine-tuned version of [google/byt5-base](https://huggingface.co/google/byt5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1413 |
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- Cer: 0.1978 |
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- Wer: 0.4524 |
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- Word Acc: 0.5476 |
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- Gen Len: 7.6457 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Cer | Wer | Word Acc | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|:-------:| |
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| No log | 0.54 | 50 | 16.1894 | 2.1868 | 2.2905 | -1.2905 | 19.0 | |
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| No log | 1.08 | 100 | 13.7479 | 2.1248 | 1.9333 | -0.9333 | 19.0 | |
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| No log | 1.61 | 150 | 11.6231 | 2.1095 | 1.4238 | -0.4238 | 18.7486 | |
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| No log | 2.15 | 200 | 8.9106 | 1.056 | 0.9857 | 0.0143 | 10.6171 | |
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| No log | 2.69 | 250 | 4.6844 | 0.8523 | 0.9762 | 0.0238 | 9.36 | |
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| No log | 3.23 | 300 | 4.1175 | 0.5756 | 0.9714 | 0.0286 | 7.4114 | |
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| No log | 3.76 | 350 | 3.3688 | 0.5951 | 0.9714 | 0.0286 | 7.8 | |
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| No log | 4.3 | 400 | 2.2287 | 0.6112 | 0.9857 | 0.0143 | 6.7543 | |
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| No log | 4.84 | 450 | 1.5164 | 0.6095 | 0.9571 | 0.0429 | 7.8857 | |
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| 8.4834 | 5.38 | 500 | 1.0363 | 0.5976 | 0.9476 | 0.0524 | 7.8229 | |
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| 8.4834 | 5.91 | 550 | 0.6893 | 0.5976 | 0.9476 | 0.0524 | 7.7943 | |
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| 8.4834 | 6.45 | 600 | 0.5438 | 0.5866 | 0.9381 | 0.0619 | 7.9943 | |
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| 8.4834 | 6.99 | 650 | 0.4720 | 0.5806 | 0.9333 | 0.0667 | 8.0057 | |
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| 8.4834 | 7.53 | 700 | 0.4305 | 0.5764 | 0.9333 | 0.0667 | 8.0057 | |
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| 8.4834 | 8.06 | 750 | 0.3931 | 0.5654 | 0.9333 | 0.0667 | 8.2971 | |
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| 8.4834 | 8.6 | 800 | 0.3450 | 0.4576 | 0.9952 | 0.0048 | 7.7086 | |
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| 8.4834 | 9.14 | 850 | 0.2773 | 0.3226 | 0.8238 | 0.1762 | 7.8743 | |
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| 8.4834 | 9.68 | 900 | 0.2184 | 0.2368 | 0.7286 | 0.2714 | 7.2171 | |
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| 8.4834 | 10.22 | 950 | 0.1992 | 0.2165 | 0.6333 | 0.3667 | 7.4343 | |
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| 0.7362 | 10.75 | 1000 | 0.1887 | 0.2097 | 0.5714 | 0.4286 | 7.5829 | |
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| 0.7362 | 11.29 | 1050 | 0.1815 | 0.2216 | 0.5905 | 0.4095 | 7.6171 | |
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| 0.7362 | 11.83 | 1100 | 0.1688 | 0.2046 | 0.5762 | 0.4238 | 7.4629 | |
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| 0.7362 | 12.37 | 1150 | 0.1679 | 0.2012 | 0.5286 | 0.4714 | 7.7143 | |
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| 0.7362 | 12.9 | 1200 | 0.1579 | 0.1952 | 0.5333 | 0.4667 | 7.5257 | |
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| 0.7362 | 13.44 | 1250 | 0.1531 | 0.1969 | 0.5095 | 0.4905 | 7.5714 | |
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| 0.7362 | 13.98 | 1300 | 0.1484 | 0.1935 | 0.4952 | 0.5048 | 7.5543 | |
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| 0.7362 | 14.52 | 1350 | 0.1481 | 0.1969 | 0.4952 | 0.5048 | 7.5886 | |
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| 0.7362 | 15.05 | 1400 | 0.1417 | 0.191 | 0.481 | 0.519 | 7.5829 | |
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| 0.7362 | 15.59 | 1450 | 0.1429 | 0.1876 | 0.4762 | 0.5238 | 7.5829 | |
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| 0.195 | 16.13 | 1500 | 0.1407 | 0.1834 | 0.481 | 0.519 | 7.48 | |
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| 0.195 | 16.67 | 1550 | 0.1409 | 0.1995 | 0.481 | 0.519 | 7.7086 | |
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| 0.195 | 17.2 | 1600 | 0.1432 | 0.1817 | 0.4762 | 0.5238 | 7.4857 | |
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| 0.195 | 17.74 | 1650 | 0.1439 | 0.1885 | 0.4762 | 0.5238 | 7.5429 | |
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| 0.195 | 18.28 | 1700 | 0.1385 | 0.1766 | 0.4476 | 0.5524 | 7.5143 | |
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| 0.195 | 18.82 | 1750 | 0.1357 | 0.1834 | 0.4762 | 0.5238 | 7.4971 | |
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| 0.195 | 19.35 | 1800 | 0.1349 | 0.1935 | 0.4714 | 0.5286 | 7.4686 | |
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| 0.195 | 19.89 | 1850 | 0.1355 | 0.1842 | 0.4286 | 0.5714 | 7.5371 | |
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| 0.195 | 20.43 | 1900 | 0.1343 | 0.1902 | 0.4619 | 0.5381 | 7.5714 | |
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| 0.195 | 20.97 | 1950 | 0.1348 | 0.1808 | 0.4619 | 0.5381 | 7.4229 | |
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| 0.1287 | 21.51 | 2000 | 0.1341 | 0.1817 | 0.4524 | 0.5476 | 7.4571 | |
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| 0.1287 | 22.04 | 2050 | 0.1324 | 0.1868 | 0.4476 | 0.5524 | 7.5371 | |
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| 0.1287 | 22.58 | 2100 | 0.1329 | 0.1859 | 0.4571 | 0.5429 | 7.4571 | |
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| 0.1287 | 23.12 | 2150 | 0.1367 | 0.1868 | 0.4476 | 0.5524 | 7.56 | |
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| 0.1287 | 23.66 | 2200 | 0.1389 | 0.1919 | 0.4667 | 0.5333 | 7.48 | |
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| 0.1287 | 24.19 | 2250 | 0.1385 | 0.18 | 0.4333 | 0.5667 | 7.5029 | |
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| 0.1287 | 24.73 | 2300 | 0.1429 | 0.1944 | 0.4905 | 0.5095 | 7.4171 | |
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| 0.1287 | 25.27 | 2350 | 0.1414 | 0.1961 | 0.4667 | 0.5333 | 7.6057 | |
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| 0.1287 | 25.81 | 2400 | 0.1419 | 0.1876 | 0.4333 | 0.5667 | 7.5371 | |
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| 0.1287 | 26.34 | 2450 | 0.1433 | 0.1927 | 0.4667 | 0.5333 | 7.5886 | |
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| 0.0977 | 26.88 | 2500 | 0.1433 | 0.1927 | 0.4571 | 0.5429 | 7.5486 | |
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| 0.0977 | 27.42 | 2550 | 0.1413 | 0.1978 | 0.4524 | 0.5476 | 7.6457 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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