Xegho.30.2 / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - bleu
model-index:
  - name: Xegho.30.2
    results: []

Xegho.30.2

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

  • Loss: 0.1632
  • Bleu: 91.1608

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: 1e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 121
  • 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 Bleu
No log 0.6 100 1.4767 23.2970
No log 1.19 200 1.0102 34.8884
No log 1.79 300 0.7680 39.9415
No log 2.38 400 0.6129 42.4210
1.2252 2.98 500 0.4962 46.5901
1.2252 3.57 600 0.4293 48.9165
1.2252 4.17 700 0.3698 50.4146
1.2252 4.76 800 0.3194 52.4519
1.2252 5.36 900 0.2836 53.0005
0.463 5.95 1000 0.2635 55.5264
0.463 6.55 1100 0.2444 57.7553
0.463 7.14 1200 0.2262 60.8152
0.463 7.74 1300 0.2205 60.3349
0.463 8.33 1400 0.2082 62.5781
0.297 8.93 1500 0.2045 62.9341
0.297 9.52 1600 0.1969 63.9225
0.297 10.12 1700 0.1939 63.9559
0.297 10.71 1800 0.1842 66.0123
0.297 11.31 1900 0.1836 65.7767
0.2403 11.9 2000 0.1807 65.1204
0.2403 12.5 2100 0.1778 65.5556
0.2403 13.1 2200 0.1753 66.2715
0.2403 13.69 2300 0.1728 67.0917
0.2403 14.29 2400 0.1716 67.2965
0.1976 14.88 2500 0.1719 66.5856
0.1976 15.48 2600 0.1706 66.7707
0.1976 16.07 2700 0.1698 66.8323
0.1976 16.67 2800 0.1705 66.8579
0.1976 17.26 2900 0.1663 67.3175
0.1747 17.86 3000 0.1671 68.2097
0.1747 18.45 3100 0.1681 68.1515
0.1747 19.05 3200 0.1650 68.6221
0.1747 19.64 3300 0.1643 68.6828
0.1747 20.24 3400 0.1662 68.9329
0.1626 20.83 3500 0.1644 68.9651
0.1626 21.43 3600 0.1660 68.6685
0.1626 22.02 3700 0.1640 68.7471
0.1626 22.62 3800 0.1630 68.6685
0.1626 23.21 3900 0.1637 68.6835
0.1437 23.81 4000 0.1632 68.5208
0.1437 24.4 4100 0.1640 68.5059
0.1437 25.0 4200 0.1645 68.5059
0.1437 25.6 4300 0.1639 68.5059

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.11.0a0+17540c5
  • Datasets 2.1.0
  • Tokenizers 0.12.1