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T5-JSON-OM-IMP

Text2Text Generation
Transformers
Safetensors
t5
Generated from Trainer
text-generation-inference
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T5-JSON-OM-IMP / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: T5-small
tags:
  - generated_from_trainer
metrics:
  - bleu
  - rouge
model-index:
  - name: T5-JSON-OM-IMP
    results: []

T5-JSON-OM-IMP

This model is a fine-tuned version of T5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0063
  • Micro Precision: 0.4069
  • Micro Recall: 0.4681
  • Micro F1: 0.4353
  • Macro Precision: 0.4072
  • Macro Recall: 0.4742
  • Macro F1: 0.4382
  • Bleu: 75.6457
  • Rouge1: 0.7665
  • Rouge2: 0.5226

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Micro Precision Micro Recall Micro F1 Macro Precision Macro Recall Macro F1 Bleu Rouge1 Rouge2
17.7048 0.1068 50 8.2715 0 0.0 0 0.0 0.0 0 0.0213 0.0194 0.0
3.5821 0.2137 100 0.1261 0 0.0 0 0.0 0.0 0 0.0022 0.0022 0.0
0.5575 0.3205 150 0.0912 0 0.0 0 0.0 0.0 0 0.0 0.0 0.0
0.1174 0.4274 200 0.0534 0 0.0 0 0.0 0.0 0 0.0 0.0 0.0
0.067 0.5342 250 0.0329 0 0.0 0 0.0 0.0 0 0.0 0.0 0.0
0.047 0.6410 300 0.0223 0 0.0 0 0.0 0.0 0 0.0000 0.0026 0.0005
0.0367 0.7479 350 0.0176 0.1667 0.0007 0.0015 0.125 0.0008 0.0015 0.0588 0.0196 0.0085
0.0305 0.8547 400 0.0151 0.3333 0.0066 0.0129 0.2500 0.0069 0.0134 0.2728 0.0411 0.0211
0.0259 0.9615 450 0.0128 0.3904 0.0536 0.0942 0.3743 0.0562 0.0978 5.1808 0.1404 0.0812
0.023 1.0684 500 0.0109 0.3549 0.1570 0.2177 0.3537 0.1627 0.2228 22.2151 0.3401 0.2093
0.0208 1.1752 550 0.0097 0.3635 0.2678 0.3084 0.3621 0.2756 0.3130 44.1481 0.5171 0.3302
0.0191 1.2821 600 0.0084 0.3442 0.3478 0.3460 0.3446 0.3517 0.3481 61.5038 0.6523 0.4297
0.017 1.3889 650 0.0080 0.3555 0.3881 0.3711 0.3555 0.3921 0.3729 67.9000 0.7144 0.4766
0.0158 1.4957 700 0.0077 0.3907 0.4299 0.4094 0.3906 0.4342 0.4112 73.1590 0.7482 0.5047
0.0151 1.6026 750 0.0073 0.3906 0.4270 0.4080 0.3905 0.4311 0.4098 74.0266 0.7572 0.5115
0.0139 1.7094 800 0.0070 0.3962 0.4453 0.4193 0.3962 0.4504 0.4216 75.0071 0.7665 0.5226
0.0135 1.8162 850 0.0069 0.4101 0.4571 0.4323 0.4106 0.4626 0.4350 75.7473 0.7674 0.5221
0.0129 1.9231 900 0.0068 0.4065 0.4563 0.4300 0.4069 0.4619 0.4327 75.3869 0.7651 0.5159
0.0125 2.0299 950 0.0067 0.3994 0.4600 0.4275 0.3995 0.4655 0.4300 75.0995 0.7644 0.5174
0.0115 2.1368 1000 0.0066 0.4059 0.4622 0.4322 0.4062 0.4678 0.4348 75.5433 0.7666 0.5209
0.0115 2.2436 1050 0.0065 0.4064 0.4637 0.4332 0.4067 0.4698 0.4360 75.5672 0.7658 0.5213
0.0114 2.3504 1100 0.0066 0.4118 0.4644 0.4366 0.4124 0.4704 0.4395 75.9796 0.7695 0.5254
0.0112 2.4573 1150 0.0065 0.4055 0.4674 0.4342 0.4057 0.4732 0.4369 75.5003 0.7654 0.5203
0.012 2.5641 1200 0.0064 0.3971 0.4585 0.4256 0.3972 0.4642 0.4281 75.0879 0.7662 0.5205
0.0107 2.6709 1250 0.0064 0.3883 0.4490 0.4165 0.3885 0.4550 0.4191 74.6715 0.7654 0.5178
0.0103 2.7778 1300 0.0064 0.3981 0.4585 0.4262 0.3983 0.4645 0.4289 75.1906 0.7673 0.5222
0.0106 2.8846 1350 0.0064 0.3985 0.4578 0.4261 0.3987 0.4639 0.4288 75.2734 0.7661 0.5196
0.0099 2.9915 1400 0.0064 0.4082 0.4681 0.4361 0.4085 0.4741 0.4389 75.6457 0.7656 0.5220
0.0101 3.0983 1450 0.0064 0.4028 0.4622 0.4305 0.4031 0.4680 0.4331 75.4024 0.7658 0.5199
0.0101 3.2051 1500 0.0064 0.4028 0.4607 0.4298 0.4031 0.4663 0.4324 75.3197 0.7648 0.5179
0.01 3.3120 1550 0.0064 0.4074 0.4666 0.4350 0.4078 0.4726 0.4378 75.5829 0.7650 0.5206
0.0095 3.4188 1600 0.0063 0.4078 0.4688 0.4362 0.4081 0.4749 0.4390 75.6771 0.7665 0.5231
0.0099 3.5256 1650 0.0063 0.4075 0.4688 0.4360 0.4078 0.4748 0.4388 75.6573 0.7662 0.5226
0.0098 3.6325 1700 0.0063 0.4069 0.4681 0.4353 0.4072 0.4742 0.4382 75.6457 0.7665 0.5226
0.0093 3.7393 1750 0.0063 0.4071 0.4681 0.4355 0.4075 0.4742 0.4383 75.6457 0.7658 0.5221
0.0095 3.8462 1800 0.0063 0.4065 0.4674 0.4348 0.4068 0.4736 0.4377 75.6341 0.7660 0.5221
0.0095 3.9530 1850 0.0063 0.4069 0.4681 0.4353 0.4072 0.4742 0.4382 75.6457 0.7665 0.5226

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.3.1
  • Tokenizers 0.21.0