--- license: apache-2.0 base_model: Demosthene-OR/t5-base-finetuned-en-to-fr tags: - generated_from_trainer metrics: - bleu model-index: - name: t5-base-finetuned-en-to-fr results: [] --- # t5-base-finetuned-en-to-fr This model is a fine-tuned version of [Demosthene-OR/t5-base-finetuned-en-to-fr](https://huggingface.co/Demosthene-OR/t5-base-finetuned-en-to-fr) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0002 - Bleu: 100.0 - Gen Len: 7.3846 ## 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| | No log | 1.0 | 1 | 0.2559 | 93.25 | 7.0 | | No log | 2.0 | 2 | 0.2298 | 93.25 | 7.0 | | No log | 3.0 | 3 | 0.2035 | 93.25 | 7.0 | | No log | 4.0 | 4 | 0.1798 | 93.25 | 7.0 | | No log | 5.0 | 5 | 0.1574 | 93.25 | 7.0 | | No log | 6.0 | 6 | 0.1374 | 93.25 | 7.0 | | No log | 7.0 | 7 | 0.1164 | 93.25 | 7.0 | | No log | 8.0 | 8 | 0.0963 | 93.25 | 7.0 | | No log | 9.0 | 9 | 0.0824 | 97.2544 | 7.0769 | | No log | 10.0 | 10 | 0.0749 | 97.8023 | 7.0769 | | No log | 11.0 | 11 | 0.0697 | 97.8023 | 7.0769 | | No log | 12.0 | 12 | 0.0658 | 97.8023 | 7.0769 | | No log | 13.0 | 13 | 0.0616 | 97.8023 | 7.0769 | | No log | 14.0 | 14 | 0.0572 | 97.8023 | 7.0769 | | No log | 15.0 | 15 | 0.0525 | 97.8023 | 7.0769 | | No log | 16.0 | 16 | 0.0485 | 97.8023 | 7.0769 | | No log | 17.0 | 17 | 0.0443 | 97.8023 | 7.0769 | | No log | 18.0 | 18 | 0.0404 | 97.8023 | 7.0769 | | No log | 19.0 | 19 | 0.0360 | 97.8023 | 7.0769 | | No log | 20.0 | 20 | 0.0325 | 97.8023 | 7.0769 | | No log | 21.0 | 21 | 0.0276 | 97.8023 | 7.0769 | | No log | 22.0 | 22 | 0.0229 | 97.8023 | 7.0769 | | No log | 23.0 | 23 | 0.0186 | 97.8023 | 7.0769 | | No log | 24.0 | 24 | 0.0149 | 97.8023 | 7.0769 | | No log | 25.0 | 25 | 0.0116 | 97.8023 | 7.0769 | | No log | 26.0 | 26 | 0.0083 | 100.0 | 7.3846 | | No log | 27.0 | 27 | 0.0060 | 100.0 | 7.3846 | | No log | 28.0 | 28 | 0.0042 | 100.0 | 7.3846 | | No log | 29.0 | 29 | 0.0029 | 100.0 | 7.3846 | | No log | 30.0 | 30 | 0.0021 | 100.0 | 7.3846 | | No log | 31.0 | 31 | 0.0015 | 100.0 | 7.3846 | | No log | 32.0 | 32 | 0.0011 | 100.0 | 7.3846 | | No log | 33.0 | 33 | 0.0008 | 100.0 | 7.3846 | | No log | 34.0 | 34 | 0.0007 | 100.0 | 7.3846 | | No log | 35.0 | 35 | 0.0005 | 100.0 | 7.3846 | | No log | 36.0 | 36 | 0.0005 | 100.0 | 7.3846 | | No log | 37.0 | 37 | 0.0004 | 100.0 | 7.3846 | | No log | 38.0 | 38 | 0.0004 | 100.0 | 7.3846 | | No log | 39.0 | 39 | 0.0003 | 100.0 | 7.3846 | | No log | 40.0 | 40 | 0.0003 | 100.0 | 7.3846 | | No log | 41.0 | 41 | 0.0003 | 100.0 | 7.3846 | | No log | 42.0 | 42 | 0.0003 | 100.0 | 7.3846 | | No log | 43.0 | 43 | 0.0003 | 100.0 | 7.3846 | | No log | 44.0 | 44 | 0.0002 | 100.0 | 7.3846 | | No log | 45.0 | 45 | 0.0002 | 100.0 | 7.3846 | | No log | 46.0 | 46 | 0.0002 | 100.0 | 7.3846 | | No log | 47.0 | 47 | 0.0002 | 100.0 | 7.3846 | | No log | 48.0 | 48 | 0.0002 | 100.0 | 7.3846 | | No log | 49.0 | 49 | 0.0002 | 100.0 | 7.3846 | | No log | 50.0 | 50 | 0.0002 | 100.0 | 7.3846 | | No log | 51.0 | 51 | 0.0002 | 100.0 | 7.3846 | | No log | 52.0 | 52 | 0.0002 | 100.0 | 7.3846 | | No log | 53.0 | 53 | 0.0002 | 100.0 | 7.3846 | | No log | 54.0 | 54 | 0.0002 | 100.0 | 7.3846 | | No log | 55.0 | 55 | 0.0002 | 100.0 | 7.3846 | | No log | 56.0 | 56 | 0.0002 | 100.0 | 7.3846 | | No log | 57.0 | 57 | 0.0002 | 100.0 | 7.3846 | | No log | 58.0 | 58 | 0.0002 | 100.0 | 7.3846 | | No log | 59.0 | 59 | 0.0002 | 100.0 | 7.3846 | | No log | 60.0 | 60 | 0.0002 | 100.0 | 7.3846 | | No log | 61.0 | 61 | 0.0002 | 100.0 | 7.3846 | | No log | 62.0 | 62 | 0.0002 | 100.0 | 7.3846 | | No log | 63.0 | 63 | 0.0002 | 100.0 | 7.3846 | | No log | 64.0 | 64 | 0.0002 | 100.0 | 7.3846 | | No log | 65.0 | 65 | 0.0002 | 100.0 | 7.3846 | | No log | 66.0 | 66 | 0.0002 | 100.0 | 7.3846 | | No log | 67.0 | 67 | 0.0002 | 100.0 | 7.3846 | | No log | 68.0 | 68 | 0.0002 | 100.0 | 7.3846 | | No log | 69.0 | 69 | 0.0002 | 100.0 | 7.3846 | | No log | 70.0 | 70 | 0.0002 | 100.0 | 7.3846 | | No log | 71.0 | 71 | 0.0002 | 100.0 | 7.3846 | | No log | 72.0 | 72 | 0.0002 | 100.0 | 7.3846 | | No log | 73.0 | 73 | 0.0002 | 100.0 | 7.3846 | | No log | 74.0 | 74 | 0.0002 | 100.0 | 7.3846 | | No log | 75.0 | 75 | 0.0002 | 100.0 | 7.3846 | | No log | 76.0 | 76 | 0.0002 | 100.0 | 7.3846 | | No log | 77.0 | 77 | 0.0002 | 100.0 | 7.3846 | | No log | 78.0 | 78 | 0.0002 | 100.0 | 7.3846 | | No log | 79.0 | 79 | 0.0002 | 100.0 | 7.3846 | | No log | 80.0 | 80 | 0.0002 | 100.0 | 7.3846 | | No log | 81.0 | 81 | 0.0002 | 100.0 | 7.3846 | | No log | 82.0 | 82 | 0.0002 | 100.0 | 7.3846 | | No log | 83.0 | 83 | 0.0002 | 100.0 | 7.3846 | | No log | 84.0 | 84 | 0.0002 | 100.0 | 7.3846 | | No log | 85.0 | 85 | 0.0002 | 100.0 | 7.3846 | | No log | 86.0 | 86 | 0.0002 | 100.0 | 7.3846 | | No log | 87.0 | 87 | 0.0002 | 100.0 | 7.3846 | | No log | 88.0 | 88 | 0.0002 | 100.0 | 7.3846 | | No log | 89.0 | 89 | 0.0002 | 100.0 | 7.3846 | | No log | 90.0 | 90 | 0.0002 | 100.0 | 7.3846 | | No log | 91.0 | 91 | 0.0002 | 100.0 | 7.3846 | | No log | 92.0 | 92 | 0.0002 | 100.0 | 7.3846 | | No log | 93.0 | 93 | 0.0002 | 100.0 | 7.3846 | | No log | 94.0 | 94 | 0.0002 | 100.0 | 7.3846 | | No log | 95.0 | 95 | 0.0002 | 100.0 | 7.3846 | | No log | 96.0 | 96 | 0.0002 | 100.0 | 7.3846 | | No log | 97.0 | 97 | 0.0002 | 100.0 | 7.3846 | | No log | 98.0 | 98 | 0.0002 | 100.0 | 7.3846 | | No log | 99.0 | 99 | 0.0002 | 100.0 | 7.3846 | | No log | 100.0 | 100 | 0.0002 | 100.0 | 7.3846 | ### Framework versions - Transformers 4.33.1 - Pytorch 2.0.1 - Datasets 2.13.0 - Tokenizers 0.13.2