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my_awesome_opus_books_model

Text2Text Generation
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TensorBoard
Safetensors
t5
Generated from Trainer
text-generation-inference
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my_awesome_opus_books_model / README.md
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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
metrics:
  - bleu
model-index:
  - name: my_awesome_opus_books_model
    results: []

my_awesome_opus_books_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: 3.2918
  • Bleu: 0.006
  • 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
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
No log 1.0 15 6.5275 0.0014 19.0
No log 2.0 30 5.6262 0.0017 18.9333
No log 3.0 45 5.3621 0.0012 19.0
No log 4.0 60 5.1888 0.0003 19.0
No log 5.0 75 5.0467 0.0005 19.0
No log 6.0 90 4.9398 0.0004 19.0
No log 7.0 105 4.8270 0.0004 19.0
No log 8.0 120 4.7307 0.0004 19.0
No log 9.0 135 4.6413 0.0006 19.0
No log 10.0 150 4.5564 0.001 19.0
No log 11.0 165 4.4810 0.0068 19.0
No log 12.0 180 4.4120 0.0102 19.0
No log 13.0 195 4.3472 0.0072 19.0
No log 14.0 210 4.2857 0.0038 19.0
No log 15.0 225 4.2197 0.0037 19.0
No log 16.0 240 4.1564 0.0028 19.0
No log 17.0 255 4.0921 0.0018 19.0
No log 18.0 270 4.0299 0.0018 19.0
No log 19.0 285 3.9678 0.0019 19.0
No log 20.0 300 3.9072 0.0007 19.0
No log 21.0 315 3.8477 0.0043 19.0
No log 22.0 330 3.7894 0.0024 19.0
No log 23.0 345 3.7494 0.0 19.0
No log 24.0 360 3.7120 0.0 19.0
No log 25.0 375 3.6799 0.0007 19.0
No log 26.0 390 3.6512 0.0 19.0
No log 27.0 405 3.6272 0.0 19.0
No log 28.0 420 3.6106 0.0 19.0
No log 29.0 435 3.5992 0.0059 19.0
No log 30.0 450 3.5872 0.0007 19.0
No log 31.0 465 3.5728 0.0004 19.0
No log 32.0 480 3.5575 0.0004 19.0
No log 33.0 495 3.5474 0.001 19.0
4.6099 34.0 510 3.5393 0.001 19.0
4.6099 35.0 525 3.5271 0.0009 19.0
4.6099 36.0 540 3.5240 0.0015 19.0
4.6099 37.0 555 3.5154 0.0011 18.8833
4.6099 38.0 570 3.5015 0.0005 18.85
4.6099 39.0 585 3.4891 0.0005 18.8
4.6099 40.0 600 3.4856 0.0005 18.8
4.6099 41.0 615 3.4791 0.0005 18.8
4.6099 42.0 630 3.4646 0.0004 18.8
4.6099 43.0 645 3.4589 0.0004 18.8
4.6099 44.0 660 3.4497 0.0005 18.8
4.6099 45.0 675 3.4436 0.0005 18.8
4.6099 46.0 690 3.4382 0.0005 18.8
4.6099 47.0 705 3.4330 0.0005 18.8
4.6099 48.0 720 3.4217 0.0005 18.8
4.6099 49.0 735 3.4135 0.0005 18.8
4.6099 50.0 750 3.4096 0.0006 18.8
4.6099 51.0 765 3.4013 0.0007 18.8
4.6099 52.0 780 3.3969 0.0007 18.8
4.6099 53.0 795 3.3906 0.0006 18.8
4.6099 54.0 810 3.3819 0.0008 18.8
4.6099 55.0 825 3.3799 0.0009 18.8
4.6099 56.0 840 3.3753 0.001 18.8
4.6099 57.0 855 3.3742 0.0012 18.8
4.6099 58.0 870 3.3641 0.0008 18.8
4.6099 59.0 885 3.3604 0.0009 18.8
4.6099 60.0 900 3.3554 0.0009 18.8
4.6099 61.0 915 3.3522 0.0016 18.8
4.6099 62.0 930 3.3494 0.001 18.8
4.6099 63.0 945 3.3454 0.0022 19.0
4.6099 64.0 960 3.3441 0.003 19.0
4.6099 65.0 975 3.3391 0.0035 18.8
4.6099 66.0 990 3.3366 0.0022 18.8
3.4904 67.0 1005 3.3340 0.0018 18.8
3.4904 68.0 1020 3.3303 0.0023 19.0
3.4904 69.0 1035 3.3304 0.0024 19.0
3.4904 70.0 1050 3.3284 0.0019 19.0
3.4904 71.0 1065 3.3260 0.0032 19.0
3.4904 72.0 1080 3.3246 0.0021 19.0
3.4904 73.0 1095 3.3186 0.0022 19.0
3.4904 74.0 1110 3.3150 0.0021 19.0
3.4904 75.0 1125 3.3144 0.0022 19.0
3.4904 76.0 1140 3.3121 0.0026 19.0
3.4904 77.0 1155 3.3131 0.0024 19.0
3.4904 78.0 1170 3.3118 0.0021 19.0
3.4904 79.0 1185 3.3092 0.0025 19.0
3.4904 80.0 1200 3.3095 0.0022 19.0
3.4904 81.0 1215 3.3059 0.003 19.0
3.4904 82.0 1230 3.3015 0.0016 19.0
3.4904 83.0 1245 3.3004 0.0024 19.0
3.4904 84.0 1260 3.3002 0.0018 19.0
3.4904 85.0 1275 3.2994 0.0021 19.0
3.4904 86.0 1290 3.2979 0.002 19.0
3.4904 87.0 1305 3.2955 0.0019 19.0
3.4904 88.0 1320 3.2940 0.003 19.0
3.4904 89.0 1335 3.2942 0.0021 19.0
3.4904 90.0 1350 3.2948 0.0023 19.0
3.4904 91.0 1365 3.2939 0.0024 19.0
3.4904 92.0 1380 3.2934 0.004 19.0
3.4904 93.0 1395 3.2928 0.0032 19.0
3.4904 94.0 1410 3.2925 0.0059 19.0
3.4904 95.0 1425 3.2922 0.004 19.0
3.4904 96.0 1440 3.2920 0.0047 19.0
3.4904 97.0 1455 3.2920 0.0052 19.0
3.4904 98.0 1470 3.2918 0.0062 19.0
3.4904 99.0 1485 3.2918 0.0076 19.0
3.2991 100.0 1500 3.2918 0.006 19.0

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.2