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hrezaei
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T5LAA

Text2Text Generation
Transformers
Safetensors
t5la
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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  1. README.md +263 -0
  2. generation_config.json +7 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: T5LAA
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # T5LAA
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 4.8058
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+ - Accuracy: 0.0279
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 2
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+ - total_train_batch_size: 16
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+ - total_eval_batch_size: 16
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - training_steps: 200000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:------:|:---------------:|:--------:|
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+ | 8.7605 | 0.005 | 1000 | 8.5073 | 0.0339 |
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+ | 8.0954 | 0.01 | 2000 | 8.0179 | 0.0310 |
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+ | 7.7188 | 0.015 | 3000 | 7.6839 | 0.0308 |
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+ | 7.4459 | 0.02 | 4000 | 7.4330 | 0.0329 |
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+ | 7.2526 | 0.025 | 5000 | 7.2564 | 0.0323 |
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+ | 7.1018 | 0.03 | 6000 | 7.1287 | 0.0335 |
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+ | 7.014 | 0.035 | 7000 | 7.0243 | 0.0341 |
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+ | 6.9585 | 0.04 | 8000 | 6.9537 | 0.0316 |
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+ | 6.9082 | 0.045 | 9000 | 6.8731 | 0.0329 |
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+ | 6.8857 | 0.05 | 10000 | 6.8224 | 0.0326 |
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+ | 6.8166 | 0.055 | 11000 | 6.8210 | 0.0324 |
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+ | 6.8225 | 0.06 | 12000 | 6.7650 | 0.0334 |
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+ | 6.791 | 0.065 | 13000 | 6.7341 | 0.0322 |
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+ | 6.7786 | 0.07 | 14000 | 6.7270 | 0.0329 |
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+ | 6.7516 | 0.075 | 15000 | 6.6738 | 0.0336 |
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+ | 6.7343 | 0.08 | 16000 | 6.6957 | 0.0337 |
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+ | 6.7027 | 0.085 | 17000 | 6.6473 | 0.0333 |
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+ | 6.6741 | 0.09 | 18000 | 6.6254 | 0.0345 |
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+ | 6.6426 | 0.095 | 19000 | 6.6426 | 0.0339 |
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+ | 6.6475 | 0.1 | 20000 | 6.6046 | 0.0330 |
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+ | 6.6649 | 0.105 | 21000 | 6.5704 | 0.0342 |
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+ | 6.619 | 0.11 | 22000 | 6.5711 | 0.0324 |
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+ | 6.6216 | 0.115 | 23000 | 6.5813 | 0.0320 |
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+ | 6.5812 | 0.12 | 24000 | 6.5470 | 0.0331 |
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+ | 6.5995 | 0.125 | 25000 | 6.5184 | 0.0338 |
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+ | 6.5891 | 0.13 | 26000 | 6.5082 | 0.0333 |
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+ | 6.5767 | 0.135 | 27000 | 6.4814 | 0.0328 |
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+ | 6.5387 | 0.14 | 28000 | 6.5033 | 0.0324 |
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+ | 6.5427 | 0.145 | 29000 | 6.4800 | 0.0319 |
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+ | 6.5139 | 0.15 | 30000 | 6.4772 | 0.0314 |
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+ | 6.5186 | 0.155 | 31000 | 6.4465 | 0.0323 |
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+ | 6.5233 | 0.16 | 32000 | 6.4228 | 0.0326 |
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+ | 6.4659 | 0.165 | 33000 | 6.4369 | 0.0318 |
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+ | 6.4819 | 0.17 | 34000 | 6.3976 | 0.0338 |
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+ | 6.4735 | 0.175 | 35000 | 6.4116 | 0.0330 |
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+ | 6.4659 | 0.18 | 36000 | 6.4191 | 0.0313 |
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+ | 6.443 | 0.185 | 37000 | 6.3790 | 0.0323 |
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+ | 6.448 | 0.19 | 38000 | 6.3910 | 0.0316 |
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+ | 6.421 | 0.195 | 39000 | 6.3719 | 0.0322 |
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+ | 6.4127 | 0.2 | 40000 | 6.3744 | 0.0320 |
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+ | 6.4213 | 0.205 | 41000 | 6.3811 | 0.0315 |
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+ | 6.42 | 0.21 | 42000 | 6.3516 | 0.0311 |
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+ | 6.414 | 0.215 | 43000 | 6.3339 | 0.0310 |
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+ | 6.3899 | 0.22 | 44000 | 6.3502 | 0.0315 |
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+ | 6.3715 | 1.0017 | 45000 | 6.3191 | 0.0314 |
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+ | 6.3588 | 1.0067 | 46000 | 6.3087 | 0.0315 |
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+ | 6.3802 | 1.0117 | 47000 | 6.2925 | 0.0315 |
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+ | 6.3708 | 1.0167 | 48000 | 6.3044 | 0.0318 |
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+ | 6.3189 | 1.0217 | 49000 | 6.3186 | 0.0308 |
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+ | 6.3545 | 1.0267 | 50000 | 6.3024 | 0.0307 |
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+ | 6.3255 | 1.0317 | 51000 | 6.3016 | 0.0306 |
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+ | 6.3162 | 1.0367 | 52000 | 6.2832 | 0.0317 |
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+ | 6.309 | 1.0417 | 53000 | 6.2734 | 0.0305 |
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+ | 6.314 | 1.0467 | 54000 | 6.2505 | 0.0312 |
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+ | 6.293 | 1.0517 | 55000 | 6.2592 | 0.0317 |
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+ | 6.2813 | 1.0567 | 56000 | 6.2271 | 0.0308 |
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+ | 6.2781 | 1.0617 | 57000 | 6.2520 | 0.0305 |
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+ | 6.2625 | 1.0667 | 58000 | 6.2200 | 0.0309 |
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+ | 6.2638 | 1.0717 | 59000 | 6.1990 | 0.0301 |
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+ | 6.2455 | 1.0767 | 60000 | 6.2035 | 0.0311 |
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+ | 6.253 | 1.0817 | 61000 | 6.2160 | 0.0314 |
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+ | 6.2408 | 1.0867 | 62000 | 6.2086 | 0.0301 |
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+ | 6.2332 | 1.0917 | 63000 | 6.1925 | 0.0298 |
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+ | 6.2182 | 1.0967 | 64000 | 6.1664 | 0.0304 |
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+ | 6.2301 | 1.1017 | 65000 | 6.1583 | 0.0303 |
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+ | 6.2379 | 1.1067 | 66000 | 6.1884 | 0.0305 |
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+ | 6.2211 | 1.1117 | 67000 | 6.1614 | 0.0311 |
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+ | 6.2018 | 1.1167 | 68000 | 6.1608 | 0.0307 |
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+ | 6.1969 | 1.1217 | 69000 | 6.1333 | 0.0305 |
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+ | 6.1989 | 1.1267 | 70000 | 6.1314 | 0.0302 |
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+ | 6.2058 | 1.1317 | 71000 | 6.1510 | 0.0299 |
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+ | 6.1994 | 1.1367 | 72000 | 6.1442 | 0.0295 |
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+ | 6.1715 | 1.1417 | 73000 | 6.1396 | 0.0299 |
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+ | 6.1849 | 1.1467 | 74000 | 6.1083 | 0.0300 |
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+ | 6.1709 | 1.1517 | 75000 | 6.0837 | 0.0302 |
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+ | 6.1669 | 1.1567 | 76000 | 6.0925 | 0.0292 |
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+ | 6.16 | 1.1617 | 77000 | 6.0939 | 0.0292 |
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+ | 6.1637 | 1.1667 | 78000 | 6.0950 | 0.0297 |
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+ | 6.1446 | 1.1717 | 79000 | 6.0897 | 0.0293 |
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+ | 6.1231 | 1.1767 | 80000 | 6.0780 | 0.0298 |
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+ | 6.1287 | 1.1817 | 81000 | 6.0912 | 0.0290 |
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+ | 6.1196 | 1.1867 | 82000 | 6.0849 | 0.0290 |
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+ | 6.1136 | 1.1917 | 83000 | 6.0616 | 0.0294 |
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+ | 6.1135 | 1.1967 | 84000 | 6.0516 | 0.0291 |
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+ | 6.1157 | 1.2017 | 85000 | 6.0517 | 0.0296 |
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+ | 6.1102 | 1.2067 | 86000 | 6.0622 | 0.0291 |
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+ | 6.1218 | 1.2117 | 87000 | 6.0639 | 0.0285 |
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+ | 6.1104 | 1.2167 | 88000 | 6.0515 | 0.0290 |
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+ | 6.0777 | 1.2217 | 89000 | 6.0191 | 0.0295 |
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+ | 6.051 | 2.0035 | 90000 | 6.0048 | 0.0287 |
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+ | 6.065 | 2.0085 | 91000 | 6.0302 | 0.0288 |
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+ | 6.0941 | 2.0135 | 92000 | 6.0298 | 0.0284 |
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+ | 6.0833 | 2.0185 | 93000 | 6.0141 | 0.0287 |
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+ | 6.0816 | 2.0235 | 94000 | 6.0137 | 0.0281 |
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+ | 6.0771 | 2.0285 | 95000 | 6.0285 | 0.0290 |
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+ | 6.0646 | 2.0335 | 96000 | 6.0099 | 0.0277 |
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+ | 6.0421 | 2.0385 | 97000 | 6.0031 | 0.0294 |
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+ | 6.0477 | 2.0435 | 98000 | 5.9979 | 0.0280 |
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+ | 6.0317 | 2.0485 | 99000 | 5.9879 | 0.0286 |
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+ | 6.0236 | 2.0535 | 100000 | 5.9789 | 0.0286 |
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+ | 6.0245 | 2.0585 | 101000 | 5.9813 | 0.0286 |
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+ | 6.0046 | 2.0635 | 102000 | 5.9600 | 0.0272 |
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+ | 6.0089 | 2.0685 | 103000 | 5.9696 | 0.0282 |
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+ | 6.0268 | 2.0735 | 104000 | 5.9631 | 0.0284 |
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+ | 6.015 | 2.0785 | 105000 | 5.9860 | 0.0279 |
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+ | 5.9978 | 2.0835 | 106000 | 5.9594 | 0.0282 |
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+ | 6.0095 | 2.0885 | 107000 | 5.9667 | 0.0280 |
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+ | 6.008 | 2.0935 | 108000 | 5.9561 | 0.0275 |
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+ | 5.9912 | 2.0985 | 109000 | 5.9748 | 0.0278 |
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+ | 6.0 | 2.1035 | 110000 | 5.9513 | 0.0279 |
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+ | 5.9981 | 2.1085 | 111000 | 5.9358 | 0.0277 |
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+ | 5.9877 | 2.1135 | 112000 | 5.9350 | 0.0279 |
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+ | 5.9726 | 2.1185 | 113000 | 5.9340 | 0.0278 |
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+ | 5.9696 | 2.1235 | 114000 | 5.9248 | 0.0274 |
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+ | 5.9842 | 2.1285 | 115000 | 5.9515 | 0.0273 |
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+ | 5.9919 | 2.1335 | 116000 | 5.9237 | 0.0277 |
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+ | 5.972 | 2.1385 | 117000 | 5.9278 | 0.0270 |
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+ | 5.9715 | 2.1435 | 118000 | 5.9110 | 0.0268 |
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+ | 5.9727 | 2.1485 | 119000 | 5.9139 | 0.0275 |
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+ | 5.9427 | 2.1535 | 120000 | 5.9278 | 0.0273 |
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+ | 5.9514 | 2.1585 | 121000 | 5.9227 | 0.0269 |
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+ | 5.9217 | 2.1635 | 122000 | 5.9305 | 0.0273 |
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+ | 5.9862 | 2.1685 | 123000 | 5.9092 | 0.0267 |
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+ | 5.9388 | 2.1735 | 124000 | 5.8899 | 0.0270 |
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+ | 5.9429 | 2.1785 | 125000 | 5.8950 | 0.0267 |
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+ | 5.9317 | 2.1835 | 126000 | 5.9110 | 0.0268 |
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+ | 5.9367 | 2.1885 | 127000 | 5.8681 | 0.0268 |
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+ | 5.9273 | 2.1935 | 128000 | 5.8802 | 0.0274 |
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+ | 5.934 | 2.1985 | 129000 | 5.8973 | 0.0268 |
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+ | 5.9229 | 2.2035 | 130000 | 5.8916 | 0.0270 |
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+ | 5.942 | 2.2085 | 131000 | 5.8965 | 0.0266 |
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+ | 5.9224 | 2.2135 | 132000 | 5.8800 | 0.0268 |
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+ | 5.936 | 2.2185 | 133000 | 5.8693 | 0.0269 |
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+ | 5.9129 | 3.0002 | 134000 | 5.8501 | 0.0265 |
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+ | 5.8787 | 3.0052 | 135000 | 5.8702 | 0.0267 |
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+ | 5.9171 | 3.0102 | 136000 | 5.8449 | 0.0269 |
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+ | 5.8931 | 3.0152 | 137000 | 5.8457 | 0.0270 |
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+ | 5.8612 | 3.0202 | 138000 | 5.8630 | 0.0263 |
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+ | 5.8897 | 3.0252 | 139000 | 5.8497 | 0.0267 |
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+ | 5.8772 | 3.0302 | 140000 | 5.8177 | 0.0263 |
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+ | 5.8774 | 3.0352 | 141000 | 5.8212 | 0.0266 |
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+ | 5.8694 | 3.0402 | 142000 | 5.8374 | 0.0267 |
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+ | 5.8561 | 3.0452 | 143000 | 5.7928 | 0.0267 |
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+ | 5.8658 | 3.0502 | 144000 | 5.7936 | 0.0269 |
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+ | 5.8295 | 3.0552 | 145000 | 5.7956 | 0.0265 |
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+ | 5.8444 | 3.0602 | 146000 | 5.7924 | 0.0264 |
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+ | 5.8318 | 3.0652 | 147000 | 5.7651 | 0.0265 |
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+ | 5.8323 | 3.0702 | 148000 | 5.7701 | 0.0268 |
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+ | 5.8239 | 3.0752 | 149000 | 5.7793 | 0.0264 |
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+ | 5.8057 | 3.0802 | 150000 | 5.7676 | 0.0274 |
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+ | 5.7818 | 3.0852 | 151000 | 5.7569 | 0.0270 |
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+ | 5.773 | 3.0902 | 152000 | 5.7408 | 0.0267 |
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+ | 5.7491 | 3.0952 | 153000 | 5.7206 | 0.0274 |
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+ | 5.7655 | 3.1002 | 154000 | 5.7095 | 0.0268 |
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+ | 5.7706 | 3.1052 | 155000 | 5.7079 | 0.0272 |
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+ | 5.7379 | 3.1102 | 156000 | 5.6919 | 0.0273 |
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+ | 5.7374 | 3.1152 | 157000 | 5.6678 | 0.0274 |
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+ | 5.7077 | 3.1202 | 158000 | 5.6482 | 0.0270 |
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+ | 5.7176 | 3.1252 | 159000 | 5.6142 | 0.0274 |
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+ | 5.7077 | 3.1302 | 160000 | 5.6299 | 0.0275 |
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+ | 5.6882 | 3.1352 | 161000 | 5.5914 | 0.0275 |
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+ | 5.6513 | 3.1402 | 162000 | 5.5857 | 0.0272 |
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+ | 5.6516 | 3.1452 | 163000 | 5.5584 | 0.0274 |
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+ | 5.6158 | 3.1502 | 164000 | 5.5223 | 0.0281 |
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+ | 5.6235 | 3.1552 | 165000 | 5.5276 | 0.0277 |
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+ | 5.6308 | 3.1602 | 166000 | 5.4992 | 0.0282 |
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+ | 5.5782 | 3.1652 | 167000 | 5.4890 | 0.0276 |
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+ | 5.5723 | 3.1702 | 168000 | 5.4436 | 0.0279 |
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+ | 5.5417 | 3.1752 | 169000 | 5.4166 | 0.0284 |
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+ | 5.5346 | 3.1802 | 170000 | 5.4036 | 0.0285 |
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+ | 5.5068 | 3.1852 | 171000 | 5.3664 | 0.0285 |
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+ | 5.5024 | 3.1902 | 172000 | 5.3372 | 0.0286 |
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+ | 5.4611 | 3.1952 | 173000 | 5.3065 | 0.0286 |
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+ | 5.4352 | 3.2002 | 174000 | 5.3051 | 0.0285 |
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+ | 5.4305 | 3.2052 | 175000 | 5.2718 | 0.0290 |
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+ | 5.4244 | 3.2102 | 176000 | 5.2341 | 0.0286 |
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+ | 5.406 | 3.2152 | 177000 | 5.1970 | 0.0287 |
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+ | 5.3693 | 3.2202 | 178000 | 5.1883 | 0.0288 |
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+ | 5.3414 | 4.0019 | 179000 | 5.1566 | 0.0287 |
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+ | 5.3252 | 4.0069 | 180000 | 5.1210 | 0.0291 |
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+ | 5.3302 | 4.0119 | 181000 | 5.1127 | 0.0290 |
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+ | 5.3112 | 4.0169 | 182000 | 5.0792 | 0.0289 |
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+ | 5.2651 | 4.0219 | 183000 | 5.0433 | 0.0291 |
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+ | 5.2623 | 4.0269 | 184000 | 5.0256 | 0.0288 |
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+ | 5.2297 | 4.0319 | 185000 | 5.0291 | 0.0287 |
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+ | 5.1991 | 4.0369 | 186000 | 4.9703 | 0.0288 |
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+ | 5.1883 | 4.0419 | 187000 | 4.9758 | 0.0287 |
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+ | 5.1854 | 4.0469 | 188000 | 4.9428 | 0.0282 |
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+ | 5.1636 | 4.0519 | 189000 | 4.9118 | 0.0284 |
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+ | 5.1356 | 4.0569 | 190000 | 4.9047 | 0.0282 |
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+ | 5.1329 | 4.0619 | 191000 | 4.8749 | 0.0283 |
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+ | 5.107 | 4.0669 | 192000 | 4.8771 | 0.0281 |
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+ | 5.1159 | 4.0719 | 193000 | 4.8562 | 0.0280 |
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+ | 5.0892 | 4.0769 | 194000 | 4.8465 | 0.0279 |
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+ | 5.083 | 4.0819 | 195000 | 4.8258 | 0.0279 |
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+ | 5.0824 | 4.0869 | 196000 | 4.8216 | 0.0280 |
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+ | 5.0774 | 4.0919 | 197000 | 4.8172 | 0.0279 |
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+ | 5.0567 | 4.0969 | 198000 | 4.8118 | 0.0278 |
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+ | 5.0657 | 4.1019 | 199000 | 4.8077 | 0.0278 |
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+ | 5.0751 | 4.1069 | 200000 | 4.8058 | 0.0279 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0.dev0
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
generation_config.json ADDED
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+ {
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+ "_from_model_config": true,
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+ "decoder_start_token_id": 0,
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+ "eos_token_id": 1,
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+ "pad_token_id": 0,
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+ "transformers_version": "4.49.0.dev0"
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+ }