--- license: apache-2.0 tags: - generated_from_trainer metrics: - bleu model-index: - name: Xegho.30.2 results: [] --- # Xegho.30.2 This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1632 - Bleu: 91.1608 ## 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: 1e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 121 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | Bleu | |:-------------:|:-----:|:----:|:---------------:|:-------:| | No log | 0.6 | 100 | 1.4767 | 23.2970 | | No log | 1.19 | 200 | 1.0102 | 34.8884 | | No log | 1.79 | 300 | 0.7680 | 39.9415 | | No log | 2.38 | 400 | 0.6129 | 42.4210 | | 1.2252 | 2.98 | 500 | 0.4962 | 46.5901 | | 1.2252 | 3.57 | 600 | 0.4293 | 48.9165 | | 1.2252 | 4.17 | 700 | 0.3698 | 50.4146 | | 1.2252 | 4.76 | 800 | 0.3194 | 52.4519 | | 1.2252 | 5.36 | 900 | 0.2836 | 53.0005 | | 0.463 | 5.95 | 1000 | 0.2635 | 55.5264 | | 0.463 | 6.55 | 1100 | 0.2444 | 57.7553 | | 0.463 | 7.14 | 1200 | 0.2262 | 60.8152 | | 0.463 | 7.74 | 1300 | 0.2205 | 60.3349 | | 0.463 | 8.33 | 1400 | 0.2082 | 62.5781 | | 0.297 | 8.93 | 1500 | 0.2045 | 62.9341 | | 0.297 | 9.52 | 1600 | 0.1969 | 63.9225 | | 0.297 | 10.12 | 1700 | 0.1939 | 63.9559 | | 0.297 | 10.71 | 1800 | 0.1842 | 66.0123 | | 0.297 | 11.31 | 1900 | 0.1836 | 65.7767 | | 0.2403 | 11.9 | 2000 | 0.1807 | 65.1204 | | 0.2403 | 12.5 | 2100 | 0.1778 | 65.5556 | | 0.2403 | 13.1 | 2200 | 0.1753 | 66.2715 | | 0.2403 | 13.69 | 2300 | 0.1728 | 67.0917 | | 0.2403 | 14.29 | 2400 | 0.1716 | 67.2965 | | 0.1976 | 14.88 | 2500 | 0.1719 | 66.5856 | | 0.1976 | 15.48 | 2600 | 0.1706 | 66.7707 | | 0.1976 | 16.07 | 2700 | 0.1698 | 66.8323 | | 0.1976 | 16.67 | 2800 | 0.1705 | 66.8579 | | 0.1976 | 17.26 | 2900 | 0.1663 | 67.3175 | | 0.1747 | 17.86 | 3000 | 0.1671 | 68.2097 | | 0.1747 | 18.45 | 3100 | 0.1681 | 68.1515 | | 0.1747 | 19.05 | 3200 | 0.1650 | 68.6221 | | 0.1747 | 19.64 | 3300 | 0.1643 | 68.6828 | | 0.1747 | 20.24 | 3400 | 0.1662 | 68.9329 | | 0.1626 | 20.83 | 3500 | 0.1644 | 68.9651 | | 0.1626 | 21.43 | 3600 | 0.1660 | 68.6685 | | 0.1626 | 22.02 | 3700 | 0.1640 | 68.7471 | | 0.1626 | 22.62 | 3800 | 0.1630 | 68.6685 | | 0.1626 | 23.21 | 3900 | 0.1637 | 68.6835 | | 0.1437 | 23.81 | 4000 | 0.1632 | 68.5208 | | 0.1437 | 24.4 | 4100 | 0.1640 | 68.5059 | | 0.1437 | 25.0 | 4200 | 0.1645 | 68.5059 | | 0.1437 | 25.6 | 4300 | 0.1639 | 68.5059 | ### Framework versions - Transformers 4.18.0 - Pytorch 1.11.0a0+17540c5 - Datasets 2.1.0 - Tokenizers 0.12.1