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ptt5-wikilingua-30epochs

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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ptt5-wikilingua-30epochs / README.md
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metadata
license: mit
base_model: unicamp-dl/ptt5-base-portuguese-vocab
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: ptt5-wikilingua-30epochs
    results: []

ptt5-wikilingua-30epochs

This model is a fine-tuned version of unicamp-dl/ptt5-base-portuguese-vocab on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9063
  • Rouge1: 0.2604
  • Rouge2: 0.1127
  • Rougel: 0.2222
  • Rougelsum: 0.2541
  • Gen Len: 18.4528

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.1668 1.0 28580 2.0384 0.2366 0.0935 0.2034 0.2311 18.2195
2.0348 2.0 57160 1.9725 0.2448 0.0998 0.2098 0.2391 18.3898
2.0152 3.0 85740 1.9346 0.2469 0.1024 0.2122 0.2414 18.2427
1.9769 4.0 114320 1.9096 0.2503 0.1047 0.2147 0.2446 18.2773
1.8471 5.0 142900 1.8957 0.253 0.1076 0.2169 0.2473 18.2612
1.8504 6.0 171480 1.8840 0.2541 0.1084 0.2179 0.2483 18.3317
1.7456 7.0 200060 1.8768 0.2547 0.1084 0.2183 0.2488 18.3634
1.7254 8.0 228640 1.8747 0.2563 0.1099 0.2196 0.2505 18.3577
1.7742 9.0 257220 1.8739 0.2562 0.11 0.2194 0.2504 18.3904
1.7211 10.0 285800 1.8667 0.2572 0.1109 0.2205 0.2513 18.3616
1.696 11.0 314380 1.8677 0.2568 0.1112 0.2204 0.251 18.349
1.6762 12.0 342960 1.8695 0.2571 0.1108 0.2202 0.2513 18.3528
1.6404 13.0 371540 1.8738 0.2582 0.1115 0.2208 0.2523 18.3909
1.6523 14.0 400120 1.8727 0.259 0.1118 0.2215 0.253 18.4077
1.626 15.0 428700 1.8736 0.2596 0.1124 0.2222 0.2537 18.4245
1.5922 16.0 457280 1.8750 0.259 0.1123 0.2215 0.253 18.4125
1.5345 17.0 485860 1.8783 0.2591 0.112 0.2214 0.2529 18.4013
1.5785 18.0 514440 1.8797 0.2588 0.112 0.2212 0.2527 18.3965
1.5097 19.0 543020 1.8868 0.2592 0.1115 0.221 0.2531 18.4567
1.5091 20.0 571600 1.8851 0.2593 0.1124 0.2216 0.2533 18.397
1.5116 21.0 600180 1.8895 0.2599 0.1124 0.2219 0.2537 18.4505
1.5351 22.0 628760 1.8901 0.2606 0.113 0.2225 0.2544 18.4369
1.5125 23.0 657340 1.8953 0.2598 0.1125 0.2218 0.2535 18.4273
1.5246 24.0 685920 1.8980 0.2609 0.1129 0.2226 0.2544 18.4464
1.5113 25.0 714500 1.8990 0.2604 0.1127 0.2221 0.2542 18.4562
1.4814 26.0 743080 1.9029 0.261 0.1133 0.223 0.2547 18.4634
1.5212 27.0 771660 1.9014 0.2606 0.1129 0.2226 0.2544 18.4458
1.4469 28.0 800240 1.9032 0.2609 0.1129 0.2226 0.2546 18.4577
1.4844 29.0 828820 1.9050 0.2602 0.1125 0.2221 0.2539 18.4553
1.4561 30.0 857400 1.9063 0.2604 0.1127 0.2222 0.2541 18.4528

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.13.3