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pakawadeep/mt5-base-finetuned-ctfl
mt5-base-finetuned-ctfl is a machine learning model from pakawadeep. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
probably proofread and complete it, then remove this comment. --
Downloads · 30 days
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6% of all-time downloads
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From the Hugging Face model README
This model is a fine-tuned version of google/mt5-base on CTFL-GEC dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Train Loss | Validation Loss | Train Rouge1 | Train Rouge2 | Train Rougel | Train Rougelsum | Train Gen Len | Epoch |
|---|---|---|---|---|---|---|---|
| 1.1067 | 1.0353 | 7.4965 | 1.6832 | 7.4257 | 7.3904 | 11.8762 | 0 |
| 0.9573 | 1.0010 | 7.9915 | 1.6832 | 7.9208 | 7.7793 | 11.9109 | 1 |
| 0.8858 | 1.0002 | 8.4866 | 2.1782 | 8.2744 | 8.2744 | 11.9158 | 2 |
| 0.8402 | 0.9827 | 8.4866 | 2.1782 | 8.2744 | 8.2744 | 11.9554 | 3 |
| 0.7900 | 0.9961 | 8.4866 | 2.1782 | 8.2744 | 8.2744 | 11.9158 | 4 |
| 0.7646 | 0.9898 | 8.4866 | 2.1782 | 8.2744 | 8.2744 | 11.9505 | 5 |
| 0.7190 | 0.9805 | 8.4866 | 2.1782 | 8.2744 | 8.2744 | 11.9208 | 6 |
| 0.7021 | 0.9683 | 8.4866 | 2.1782 | 8.2744 | 8.2744 | 11.9455 | 7 |
| 0.6613 | 0.9732 | 8.9816 | 2.1782 | 8.7694 | 8.8755 | 11.9703 | 8 |
| 0.6416 | 0.9807 | 8.4866 | 2.1782 | 8.2744 | 8.2744 | 11.9505 | 9 |
| 0.6139 | 0.9771 | 8.4866 | 2.1782 | 8.2744 | 8.2744 | 11.9307 | 10 |
| 0.5864 | 0.9723 | 8.4866 | 2.1782 | 8.2744 | 8.2744 | 11.9505 | 11 |
| 0.5844 | 0.9919 | 8.4866 | 2.1782 | 8.2744 | 8.2744 | 11.9653 | 12 |
| 0.5679 | 1.0097 | 8.4866 | 2.1782 | 8.2744 | 8.2744 | 11.9307 | 13 |
| 0.5329 | 0.9947 | 7.9915 | 1.1881 | 7.8501 | 7.7793 | 11.9554 | 14 |
| 0.5173 | 0.9877 | 8.2037 | 1.6832 | 8.0622 | 8.0269 | 11.9505 | 15 |
| 0.4823 | 0.9955 | 7.7793 | 1.1881 | 7.5318 | 7.5318 | 11.9109 | 16 |
| 0.4626 | 1.0106 | 7.9915 | 1.1881 | 7.8501 | 7.7793 | 11.9703 | 17 |
| 0.4497 | 1.0056 | 7.7793 | 1.1881 | 7.5318 | 7.5318 | 11.9109 | 18 |
| 0.4276 | 1.0341 | 7.7793 | 1.1881 | 7.5318 | 7.5318 | 11.8911 | 19 |
| 0.4056 | 1.0482 | 7.7793 | 1.1881 | 7.5318 | 7.5318 | 11.8960 | 20 |
| 0.4003 | 1.0365 | 8.2390 | 1.1881 | 7.9915 | 8.1683 | 11.9356 | 21 |
| 0.3774 | 1.0646 | 8.2390 | 1.1881 | 7.9915 | 8.1683 | 11.9158 | 22 |
| 0.3668 | 1.0713 | 8.2390 | 1.1881 | 7.9915 | 8.1683 | 11.9158 | 23 |
| 0.3539 | 1.0748 | 8.2390 | 1.1881 | 7.9915 | 8.1683 | 11.9257 | 24 |
| 0.3355 | 1.0859 | 8.0387 | 0.8911 | 7.9208 | 7.9208 | 11.8663 | 25 |
| 0.3247 | 1.0929 | 8.7694 | 1.1881 | 8.5573 | 8.5573 | 11.9356 | 26 |
| 0.3091 | 1.1147 | 8.9816 | 1.1881 | 8.8048 | 8.7871 | 11.9604 | 27 |