--- 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: [] language: - en - fr pipeline_tag: translation --- # 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: 0.0189 - Bleu: 99.5662 - Gen Len: 5.9091 ## 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: 150 ### Training results | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| | No log | 1.0 | 2 | 0.9476 | 91.8099 | 6.2727 | | No log | 2.0 | 4 | 0.8626 | 91.2967 | 6.3636 | | No log | 3.0 | 6 | 0.7928 | 91.2967 | 6.3636 | | No log | 4.0 | 8 | 0.7310 | 91.2967 | 6.3636 | | No log | 5.0 | 10 | 0.6734 | 91.2967 | 6.3636 | | No log | 6.0 | 12 | 0.6195 | 91.7685 | 6.4545 | | No log | 7.0 | 14 | 0.5711 | 92.7714 | 6.3636 | | No log | 8.0 | 16 | 0.5311 | 92.7714 | 6.3636 | | No log | 9.0 | 18 | 0.4952 | 93.8091 | 6.2727 | | No log | 10.0 | 20 | 0.4598 | 93.8091 | 6.2727 | | No log | 11.0 | 22 | 0.4246 | 93.8091 | 6.2727 | | No log | 12.0 | 24 | 0.3919 | 93.8091 | 6.2727 | | No log | 13.0 | 26 | 0.3602 | 93.8091 | 6.2727 | | No log | 14.0 | 28 | 0.3308 | 93.8091 | 6.2727 | | No log | 15.0 | 30 | 0.3050 | 93.8091 | 6.2727 | | No log | 16.0 | 32 | 0.2828 | 94.9904 | 6.2273 | | No log | 17.0 | 34 | 0.2633 | 95.4618 | 5.8636 | | No log | 18.0 | 36 | 0.2452 | 95.4618 | 5.8636 | | No log | 19.0 | 38 | 0.2278 | 96.624 | 5.8182 | | No log | 20.0 | 40 | 0.2143 | 96.0313 | 5.9545 | | No log | 21.0 | 42 | 0.2027 | 96.0313 | 5.9545 | | No log | 22.0 | 44 | 0.1921 | 96.4897 | 5.9091 | | No log | 23.0 | 46 | 0.1831 | 96.4897 | 5.9091 | | No log | 24.0 | 48 | 0.1739 | 96.4897 | 5.9091 | | No log | 25.0 | 50 | 0.1648 | 96.4897 | 5.9091 | | No log | 26.0 | 52 | 0.1570 | 96.4897 | 5.9091 | | No log | 27.0 | 54 | 0.1511 | 96.9417 | 5.8182 | | No log | 28.0 | 56 | 0.1458 | 96.9417 | 5.8182 | | No log | 29.0 | 58 | 0.1409 | 96.9417 | 5.8182 | | No log | 30.0 | 60 | 0.1377 | 96.9417 | 5.8182 | | No log | 31.0 | 62 | 0.1342 | 96.9417 | 5.8182 | | No log | 32.0 | 64 | 0.1313 | 96.9417 | 5.8182 | | No log | 33.0 | 66 | 0.1282 | 96.9417 | 5.8182 | | No log | 34.0 | 68 | 0.1252 | 96.9417 | 5.8182 | | No log | 35.0 | 70 | 0.1216 | 96.9417 | 5.8182 | | No log | 36.0 | 72 | 0.1172 | 96.9417 | 5.8182 | | No log | 37.0 | 74 | 0.1128 | 96.9417 | 5.8182 | | No log | 38.0 | 76 | 0.1094 | 96.9417 | 5.8182 | | No log | 39.0 | 78 | 0.1060 | 96.9417 | 5.8182 | | No log | 40.0 | 80 | 0.1033 | 97.3874 | 5.8636 | | No log | 41.0 | 82 | 0.1007 | 97.3874 | 5.8636 | | No log | 42.0 | 84 | 0.0978 | 97.3874 | 5.8636 | | No log | 43.0 | 86 | 0.0945 | 97.3874 | 5.8636 | | No log | 44.0 | 88 | 0.0912 | 97.3874 | 5.8636 | | No log | 45.0 | 90 | 0.0882 | 97.3874 | 5.8636 | | No log | 46.0 | 92 | 0.0855 | 97.3874 | 5.8636 | | No log | 47.0 | 94 | 0.0835 | 97.3874 | 5.8636 | | No log | 48.0 | 96 | 0.0818 | 97.3874 | 6.1364 | | No log | 49.0 | 98 | 0.0800 | 97.3874 | 6.1364 | | No log | 50.0 | 100 | 0.0781 | 97.3874 | 6.1364 | | No log | 51.0 | 102 | 0.0764 | 97.3874 | 6.1364 | | No log | 52.0 | 104 | 0.0748 | 97.3874 | 5.8636 | | No log | 53.0 | 106 | 0.0735 | 97.3874 | 5.8636 | | No log | 54.0 | 108 | 0.0726 | 97.3874 | 5.8636 | | No log | 55.0 | 110 | 0.0716 | 97.3874 | 5.8636 | | No log | 56.0 | 112 | 0.0707 | 97.3874 | 5.8636 | | No log | 57.0 | 114 | 0.0702 | 97.3874 | 5.8636 | | No log | 58.0 | 116 | 0.0705 | 97.3874 | 5.8636 | | No log | 59.0 | 118 | 0.0705 | 97.3874 | 5.8636 | | No log | 60.0 | 120 | 0.0703 | 97.3874 | 5.8636 | | No log | 61.0 | 122 | 0.0708 | 97.3874 | 5.8636 | | No log | 62.0 | 124 | 0.0707 | 97.3874 | 5.8636 | | No log | 63.0 | 126 | 0.0714 | 97.3874 | 5.8636 | | No log | 64.0 | 128 | 0.0717 | 97.3874 | 5.8636 | | No log | 65.0 | 130 | 0.0717 | 97.3874 | 5.8636 | | No log | 66.0 | 132 | 0.0707 | 97.3874 | 5.8636 | | No log | 67.0 | 134 | 0.0700 | 97.3874 | 5.8636 | | No log | 68.0 | 136 | 0.0682 | 97.3874 | 5.8636 | | No log | 69.0 | 138 | 0.0669 | 97.3874 | 5.8636 | | No log | 70.0 | 140 | 0.0652 | 97.3874 | 5.8636 | | No log | 71.0 | 142 | 0.0630 | 97.3874 | 5.8636 | | No log | 72.0 | 144 | 0.0615 | 97.3874 | 5.8636 | | No log | 73.0 | 146 | 0.0595 | 97.3874 | 5.8636 | | No log | 74.0 | 148 | 0.0580 | 97.3874 | 5.8636 | | No log | 75.0 | 150 | 0.0566 | 97.3874 | 5.8636 | | No log | 76.0 | 152 | 0.0557 | 97.3874 | 5.8636 | | No log | 77.0 | 154 | 0.0545 | 97.3874 | 5.8636 | | No log | 78.0 | 156 | 0.0535 | 97.3874 | 5.8636 | | No log | 79.0 | 158 | 0.0523 | 97.3874 | 5.8636 | | No log | 80.0 | 160 | 0.0511 | 97.3874 | 5.8636 | | No log | 81.0 | 162 | 0.0499 | 97.3874 | 5.8636 | | No log | 82.0 | 164 | 0.0490 | 97.3874 | 5.8636 | | No log | 83.0 | 166 | 0.0482 | 97.3874 | 5.8636 | | No log | 84.0 | 168 | 0.0474 | 97.3874 | 5.8636 | | No log | 85.0 | 170 | 0.0466 | 97.3874 | 5.8636 | | No log | 86.0 | 172 | 0.0458 | 97.3874 | 5.8636 | | No log | 87.0 | 174 | 0.0449 | 97.3874 | 5.8636 | | No log | 88.0 | 176 | 0.0439 | 97.3874 | 5.8636 | | No log | 89.0 | 178 | 0.0428 | 97.3874 | 5.8636 | | No log | 90.0 | 180 | 0.0423 | 97.3874 | 5.8636 | | No log | 91.0 | 182 | 0.0419 | 97.3874 | 5.8636 | | No log | 92.0 | 184 | 0.0415 | 97.3874 | 5.8636 | | No log | 93.0 | 186 | 0.0411 | 97.3874 | 5.8636 | | No log | 94.0 | 188 | 0.0409 | 97.3874 | 5.8636 | | No log | 95.0 | 190 | 0.0404 | 97.3874 | 5.8636 | | No log | 96.0 | 192 | 0.0398 | 98.4309 | 5.9091 | | No log | 97.0 | 194 | 0.0394 | 98.4309 | 5.9091 | | No log | 98.0 | 196 | 0.0391 | 98.4309 | 5.9091 | | No log | 99.0 | 198 | 0.0388 | 97.3874 | 5.8636 | | No log | 100.0 | 200 | 0.0385 | 97.3874 | 5.8636 | | No log | 101.0 | 202 | 0.0381 | 99.5662 | 5.9091 | | No log | 102.0 | 204 | 0.0373 | 99.5662 | 5.9091 | | No log | 103.0 | 206 | 0.0365 | 99.5662 | 5.9091 | | No log | 104.0 | 208 | 0.0356 | 99.5662 | 5.9091 | | No log | 105.0 | 210 | 0.0345 | 99.5662 | 5.9091 | | No log | 106.0 | 212 | 0.0334 | 99.5662 | 5.9091 | | No log | 107.0 | 214 | 0.0324 | 99.5662 | 5.9091 | | No log | 108.0 | 216 | 0.0315 | 99.5662 | 5.9091 | | No log | 109.0 | 218 | 0.0305 | 99.5662 | 5.9091 | | No log | 110.0 | 220 | 0.0294 | 99.5662 | 5.9091 | | No log | 111.0 | 222 | 0.0283 | 99.5662 | 5.9091 | | No log | 112.0 | 224 | 0.0273 | 99.5662 | 5.9091 | | No log | 113.0 | 226 | 0.0264 | 99.5662 | 5.9091 | | No log | 114.0 | 228 | 0.0257 | 99.5662 | 5.9091 | | No log | 115.0 | 230 | 0.0251 | 99.5662 | 5.9091 | | No log | 116.0 | 232 | 0.0246 | 99.5662 | 5.9091 | | No log | 117.0 | 234 | 0.0241 | 99.5662 | 5.9091 | | No log | 118.0 | 236 | 0.0237 | 99.5662 | 5.9091 | | No log | 119.0 | 238 | 0.0233 | 99.5662 | 5.9091 | | No log | 120.0 | 240 | 0.0228 | 99.5662 | 5.9091 | | No log | 121.0 | 242 | 0.0224 | 99.5662 | 5.9091 | | No log | 122.0 | 244 | 0.0221 | 99.5662 | 5.9091 | | No log | 123.0 | 246 | 0.0217 | 99.5662 | 5.9091 | | No log | 124.0 | 248 | 0.0212 | 99.5662 | 5.9091 | | No log | 125.0 | 250 | 0.0208 | 99.5662 | 5.9091 | | No log | 126.0 | 252 | 0.0204 | 99.5662 | 5.9091 | | No log | 127.0 | 254 | 0.0201 | 99.5662 | 5.9091 | | No log | 128.0 | 256 | 0.0199 | 99.5662 | 5.9091 | | No log | 129.0 | 258 | 0.0197 | 99.5662 | 5.9091 | | No log | 130.0 | 260 | 0.0197 | 99.5662 | 5.9091 | | No log | 131.0 | 262 | 0.0196 | 99.5662 | 5.9091 | | No log | 132.0 | 264 | 0.0197 | 99.5662 | 5.9091 | | No log | 133.0 | 266 | 0.0197 | 99.5662 | 5.9091 | | No log | 134.0 | 268 | 0.0196 | 99.5662 | 5.9091 | | No log | 135.0 | 270 | 0.0195 | 99.5662 | 5.9091 | | No log | 136.0 | 272 | 0.0193 | 99.5662 | 5.9091 | | No log | 137.0 | 274 | 0.0191 | 99.5662 | 5.9091 | | No log | 138.0 | 276 | 0.0190 | 99.5662 | 5.9091 | | No log | 139.0 | 278 | 0.0190 | 99.5662 | 5.9091 | | No log | 140.0 | 280 | 0.0189 | 99.5662 | 5.9091 | | No log | 141.0 | 282 | 0.0189 | 99.5662 | 5.9091 | | No log | 142.0 | 284 | 0.0189 | 99.5662 | 5.9091 | | No log | 143.0 | 286 | 0.0189 | 99.5662 | 5.9091 | | No log | 144.0 | 288 | 0.0189 | 99.5662 | 5.9091 | | No log | 145.0 | 290 | 0.0189 | 99.5662 | 5.9091 | | No log | 146.0 | 292 | 0.0189 | 99.5662 | 5.9091 | | No log | 147.0 | 294 | 0.0189 | 99.5662 | 5.9091 | | No log | 148.0 | 296 | 0.0189 | 99.5662 | 5.9091 | | No log | 149.0 | 298 | 0.0189 | 99.5662 | 5.9091 | | No log | 150.0 | 300 | 0.0189 | 99.5662 | 5.9091 | ### Framework versions - Transformers 4.33.1 - Pytorch 2.0.1 - Datasets 2.13.0 - Tokenizers 0.13.2