genz_model2 / README.md
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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
metrics:
  - bleu
model-index:
  - name: genz_model2
    results: []

genz_model2

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1282
  • Bleu: 40.1672
  • Gen Len: 15.25

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: 50

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
No log 1.0 107 1.9410 28.2848 15.4509
No log 2.0 214 1.7415 32.3881 15.3645
No log 3.0 321 1.6506 32.8796 15.5374
No log 4.0 428 1.5856 33.1982 15.5748
1.9676 5.0 535 1.5352 34.3335 15.4556
1.9676 6.0 642 1.4929 34.962 15.5187
1.9676 7.0 749 1.4595 35.459 15.535
1.9676 8.0 856 1.4316 35.6253 15.5421
1.9676 9.0 963 1.4066 35.9011 15.4953
1.5695 10.0 1070 1.3838 36.5102 15.4907
1.5695 11.0 1177 1.3608 36.2464 15.5631
1.5695 12.0 1284 1.3410 36.3368 15.5748
1.5695 13.0 1391 1.3238 37.2607 15.493
1.5695 14.0 1498 1.3092 36.9306 15.5234
1.4322 15.0 1605 1.2943 37.2516 15.5701
1.4322 16.0 1712 1.2812 37.9106 15.4696
1.4322 17.0 1819 1.2694 38.0468 15.4907
1.4322 18.0 1926 1.2559 38.0982 15.4836
1.3384 19.0 2033 1.2455 38.5418 15.4556
1.3384 20.0 2140 1.2375 38.2567 15.4463
1.3384 21.0 2247 1.2285 38.3496 15.3972
1.3384 22.0 2354 1.2182 38.6696 15.4393
1.3384 23.0 2461 1.2092 38.6524 15.4182
1.2646 24.0 2568 1.2013 38.5694 15.4346
1.2646 25.0 2675 1.1947 38.8347 15.4065
1.2646 26.0 2782 1.1893 38.7466 15.3738
1.2646 27.0 2889 1.1840 38.8294 15.3855
1.2646 28.0 2996 1.1795 38.8043 15.3738
1.2144 29.0 3103 1.1722 38.9285 15.3995
1.2144 30.0 3210 1.1691 39.1174 15.3435
1.2144 31.0 3317 1.1646 39.2841 15.3341
1.2144 32.0 3424 1.1612 39.1613 15.2687
1.1741 33.0 3531 1.1581 39.2741 15.2921
1.1741 34.0 3638 1.1528 39.3863 15.3014
1.1741 35.0 3745 1.1501 39.5385 15.264
1.1741 36.0 3852 1.1465 39.7548 15.2897
1.1741 37.0 3959 1.1448 39.8433 15.25
1.1518 38.0 4066 1.1415 39.8777 15.2243
1.1518 39.0 4173 1.1398 40.0676 15.2453
1.1518 40.0 4280 1.1384 40.0178 15.2033
1.1518 41.0 4387 1.1348 39.8617 15.278
1.1518 42.0 4494 1.1336 39.9387 15.2664
1.1216 43.0 4601 1.1322 40.1468 15.257
1.1216 44.0 4708 1.1314 40.0534 15.257
1.1216 45.0 4815 1.1305 40.1604 15.257
1.1216 46.0 4922 1.1297 40.1344 15.2523
1.112 47.0 5029 1.1290 40.1921 15.2617
1.112 48.0 5136 1.1285 40.2545 15.25
1.112 49.0 5243 1.1283 40.1672 15.25
1.112 50.0 5350 1.1282 40.1672 15.25

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.3
  • Tokenizers 0.13.3