metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: Code_Corrector_Model
results: []
Code_Corrector_Model
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9156
- Bleu: 0.0
- Gen Len: 19.0
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 | 8 | 6.6371 | 0.0 | 19.0 |
| 6.8242 | 2.0 | 16 | 5.2780 | 0.0 | 19.0 |
| 6.8242 | 3.0 | 24 | 4.4851 | 0.0 | 19.0 |
| 5.345 | 4.0 | 32 | 3.7656 | 0.0 | 19.0 |
| 5.345 | 5.0 | 40 | 3.0462 | 0.0 | 19.0 |
| 4.0321 | 6.0 | 48 | 2.4729 | 0.0 | 19.0 |
| 3.2425 | 7.0 | 56 | 2.1585 | 0.0 | 11.7931 |
| 3.2425 | 8.0 | 64 | 2.0606 | 0.0 | 0.0 |
| 2.8344 | 9.0 | 72 | 2.0090 | 0.0 | 0.0 |
| 2.8344 | 10.0 | 80 | 1.9443 | 0.0 | 0.0 |
| 2.6721 | 11.0 | 88 | 1.8702 | 0.0 | 0.0 |
| 2.6721 | 12.0 | 96 | 1.8071 | 0.0 | 0.0 |
| 2.5019 | 13.0 | 104 | 1.7541 | 0.0 | 0.0 |
| 2.3339 | 14.0 | 112 | 1.7014 | 0.0 | 0.0 |
| 2.3339 | 15.0 | 120 | 1.6502 | 0.0 | 0.0 |
| 2.2227 | 16.0 | 128 | 1.6094 | 0.0 | 0.0 |
| 2.2227 | 17.0 | 136 | 1.5746 | 0.0 | 0.0 |
| 2.1738 | 18.0 | 144 | 1.5353 | 0.0 | 0.0 |
| 2.1738 | 19.0 | 152 | 1.5066 | 0.0 | 0.0 |
| 2.054 | 20.0 | 160 | 1.4870 | 0.0 | 0.0 |
| 1.9707 | 21.0 | 168 | 1.4581 | 0.0 | 0.0 |
| 1.9707 | 22.0 | 176 | 1.4359 | 0.0 | 0.0 |
| 1.96 | 23.0 | 184 | 1.4032 | 0.0 | 0.0 |
| 1.96 | 24.0 | 192 | 1.3737 | 0.0 | 0.0 |
| 1.7402 | 25.0 | 200 | 1.3482 | 0.0 | 0.0 |
| 1.7402 | 26.0 | 208 | 1.3257 | 0.0 | 0.0 |
| 1.7044 | 27.0 | 216 | 1.3047 | 0.0 | 0.0 |
| 1.751 | 28.0 | 224 | 1.2861 | 0.0 | 0.0 |
| 1.751 | 29.0 | 232 | 1.2644 | 0.0 | 0.0 |
| 1.6414 | 30.0 | 240 | 1.2353 | 0.0 | 0.0 |
| 1.6414 | 31.0 | 248 | 1.2160 | 0.0 | 0.0 |
| 1.6418 | 32.0 | 256 | 1.1991 | 0.0 | 0.0 |
| 1.6418 | 33.0 | 264 | 1.1937 | 0.0 | 0.0 |
| 1.6258 | 34.0 | 272 | 1.1762 | 0.0 | 0.0 |
| 1.6102 | 35.0 | 280 | 1.1632 | 0.0 | 0.0 |
| 1.6102 | 36.0 | 288 | 1.1498 | 0.0 | 0.0 |
| 1.5266 | 37.0 | 296 | 1.1361 | 0.0 | 0.0 |
| 1.5266 | 38.0 | 304 | 1.1205 | 0.0 | 10.4828 |
| 1.5756 | 39.0 | 312 | 1.1108 | 0.0 | 10.4828 |
| 1.5756 | 40.0 | 320 | 1.1028 | 0.0 | 10.4828 |
| 1.5136 | 41.0 | 328 | 1.0937 | 0.0 | 10.4828 |
| 1.529 | 42.0 | 336 | 1.0837 | 0.0 | 10.4828 |
| 1.529 | 43.0 | 344 | 1.0714 | 0.0 | 11.7931 |
| 1.4738 | 44.0 | 352 | 1.0599 | 0.0 | 13.1034 |
| 1.4738 | 45.0 | 360 | 1.0514 | 0.0 | 13.1034 |
| 1.4521 | 46.0 | 368 | 1.0467 | 0.0 | 13.1034 |
| 1.4521 | 47.0 | 376 | 1.0438 | 0.0 | 13.1034 |
| 1.4758 | 48.0 | 384 | 1.0358 | 0.0 | 13.1034 |
| 1.4698 | 49.0 | 392 | 1.0264 | 0.0 | 13.1034 |
| 1.4698 | 50.0 | 400 | 1.0205 | 0.0 | 17.6897 |
| 1.3355 | 51.0 | 408 | 1.0159 | 0.0 | 18.3448 |
| 1.3355 | 52.0 | 416 | 1.0087 | 0.0 | 19.0 |
| 1.36 | 53.0 | 424 | 1.0040 | 0.0 | 19.0 |
| 1.36 | 54.0 | 432 | 1.0005 | 0.0 | 19.0 |
| 1.3025 | 55.0 | 440 | 0.9955 | 0.0 | 19.0 |
| 1.2773 | 56.0 | 448 | 0.9910 | 0.0 | 19.0 |
| 1.2773 | 57.0 | 456 | 0.9873 | 0.0 | 19.0 |
| 1.3006 | 58.0 | 464 | 0.9840 | 0.0 | 19.0 |
| 1.3006 | 59.0 | 472 | 0.9826 | 0.0 | 19.0 |
| 1.3037 | 60.0 | 480 | 0.9813 | 0.0 | 19.0 |
| 1.3037 | 61.0 | 488 | 0.9765 | 0.0 | 19.0 |
| 1.3133 | 62.0 | 496 | 0.9717 | 0.0 | 19.0 |
| 1.2601 | 63.0 | 504 | 0.9671 | 0.0 | 19.0 |
| 1.2601 | 64.0 | 512 | 0.9637 | 0.0 | 19.0 |
| 1.2442 | 65.0 | 520 | 0.9610 | 0.0 | 19.0 |
| 1.2442 | 66.0 | 528 | 0.9585 | 0.0 | 19.0 |
| 1.2394 | 67.0 | 536 | 0.9568 | 0.0 | 19.0 |
| 1.2394 | 68.0 | 544 | 0.9546 | 0.0 | 19.0 |
| 1.2746 | 69.0 | 552 | 0.9509 | 0.0 | 19.0 |
| 1.233 | 70.0 | 560 | 0.9478 | 0.0 | 19.0 |
| 1.233 | 71.0 | 568 | 0.9452 | 0.0 | 19.0 |
| 1.2382 | 72.0 | 576 | 0.9424 | 0.0 | 19.0 |
| 1.2382 | 73.0 | 584 | 0.9400 | 0.0 | 19.0 |
| 1.2603 | 74.0 | 592 | 0.9379 | 0.0 | 19.0 |
| 1.2603 | 75.0 | 600 | 0.9357 | 0.0 | 19.0 |
| 1.2028 | 76.0 | 608 | 0.9338 | 0.0 | 19.0 |
| 1.2755 | 77.0 | 616 | 0.9330 | 0.0 | 19.0 |
| 1.2755 | 78.0 | 624 | 0.9316 | 0.0 | 19.0 |
| 1.244 | 79.0 | 632 | 0.9303 | 0.0 | 19.0 |
| 1.244 | 80.0 | 640 | 0.9291 | 0.0 | 19.0 |
| 1.115 | 81.0 | 648 | 0.9281 | 0.0 | 19.0 |
| 1.115 | 82.0 | 656 | 0.9272 | 0.0 | 19.0 |
| 1.2373 | 83.0 | 664 | 0.9258 | 0.0 | 19.0 |
| 1.2035 | 84.0 | 672 | 0.9243 | 0.0 | 19.0 |
| 1.2035 | 85.0 | 680 | 0.9231 | 0.0 | 19.0 |
| 1.1881 | 86.0 | 688 | 0.9216 | 0.0 | 19.0 |
| 1.1881 | 87.0 | 696 | 0.9205 | 0.0 | 19.0 |
| 1.1713 | 88.0 | 704 | 0.9200 | 0.0 | 19.0 |
| 1.1713 | 89.0 | 712 | 0.9191 | 0.0 | 19.0 |
| 1.1984 | 90.0 | 720 | 0.9184 | 0.0 | 19.0 |
| 1.2879 | 91.0 | 728 | 0.9177 | 0.0 | 19.0 |
| 1.2879 | 92.0 | 736 | 0.9174 | 0.0 | 19.0 |
| 1.1823 | 93.0 | 744 | 0.9171 | 0.0 | 19.0 |
| 1.1823 | 94.0 | 752 | 0.9170 | 0.0 | 19.0 |
| 1.2293 | 95.0 | 760 | 0.9166 | 0.0 | 19.0 |
| 1.2293 | 96.0 | 768 | 0.9162 | 0.0 | 19.0 |
| 1.2154 | 97.0 | 776 | 0.9160 | 0.0 | 19.0 |
| 1.1625 | 98.0 | 784 | 0.9158 | 0.0 | 19.0 |
| 1.1625 | 99.0 | 792 | 0.9156 | 0.0 | 19.0 |
| 1.1679 | 100.0 | 800 | 0.9156 | 0.0 | 19.0 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3