47015772_1
This model is a fine-tuned version of openai-community/gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6501
- Accuracy: 0.0001
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: 1.41e-05
- train_batch_size: 32
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2000
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.1019 | 0.03 | 25 | 0.9747 | 0.0001 |
0.8784 | 0.06 | 50 | 0.8178 | 0.0001 |
0.8308 | 0.09 | 75 | 0.7727 | 0.0002 |
0.7975 | 0.11 | 100 | 0.7508 | 0.0001 |
0.787 | 0.14 | 125 | 0.7370 | 0.0001 |
0.7752 | 0.17 | 150 | 0.7279 | 0.0001 |
0.7703 | 0.2 | 175 | 0.7210 | 0.0001 |
0.7584 | 0.23 | 200 | 0.7157 | 0.0001 |
0.7662 | 0.26 | 225 | 0.7108 | 0.0001 |
0.7431 | 0.28 | 250 | 0.7073 | 0.0001 |
0.7437 | 0.31 | 275 | 0.7038 | 0.0001 |
0.7378 | 0.34 | 300 | 0.7006 | 0.0001 |
0.7252 | 0.37 | 325 | 0.6974 | 0.0001 |
0.7242 | 0.4 | 350 | 0.6948 | 0.0001 |
0.7284 | 0.43 | 375 | 0.6922 | 0.0001 |
0.7187 | 0.46 | 400 | 0.6898 | 0.0001 |
0.7169 | 0.48 | 425 | 0.6878 | 0.0001 |
0.723 | 0.51 | 450 | 0.6858 | 0.0001 |
0.7189 | 0.54 | 475 | 0.6834 | 0.0001 |
0.7142 | 0.57 | 500 | 0.6818 | 0.0001 |
0.7071 | 0.6 | 525 | 0.6798 | 0.0001 |
0.7131 | 0.63 | 550 | 0.6782 | 0.0001 |
0.7107 | 0.66 | 575 | 0.6768 | 0.0001 |
0.702 | 0.68 | 600 | 0.6761 | 0.0001 |
0.6937 | 0.71 | 625 | 0.6742 | 0.0001 |
0.6984 | 0.74 | 650 | 0.6732 | 0.0001 |
0.7023 | 0.77 | 675 | 0.6720 | 0.0001 |
0.7002 | 0.8 | 700 | 0.6708 | 0.0001 |
0.7057 | 0.83 | 725 | 0.6697 | 0.0001 |
0.6991 | 0.85 | 750 | 0.6687 | 0.0001 |
0.6951 | 0.88 | 775 | 0.6674 | 0.0001 |
0.7101 | 0.91 | 800 | 0.6668 | 0.0001 |
0.6931 | 0.94 | 825 | 0.6661 | 0.0001 |
0.6866 | 0.97 | 850 | 0.6652 | 0.0001 |
0.702 | 1.0 | 875 | 0.6643 | 0.0001 |
0.6996 | 1.03 | 900 | 0.6637 | 0.0001 |
0.7077 | 1.05 | 925 | 0.6629 | 0.0001 |
0.6955 | 1.08 | 950 | 0.6623 | 0.0001 |
0.6947 | 1.11 | 975 | 0.6619 | 0.0001 |
0.6933 | 1.14 | 1000 | 0.6612 | 0.0001 |
0.6855 | 1.17 | 1025 | 0.6601 | 0.0001 |
0.7004 | 1.2 | 1050 | 0.6597 | 0.0001 |
0.6934 | 1.22 | 1075 | 0.6594 | 0.0001 |
0.6863 | 1.25 | 1100 | 0.6585 | 0.0001 |
0.6886 | 1.28 | 1125 | 0.6580 | 0.0001 |
0.6851 | 1.31 | 1150 | 0.6579 | 0.0001 |
0.683 | 1.34 | 1175 | 0.6574 | 0.0001 |
0.703 | 1.37 | 1200 | 0.6570 | 0.0001 |
0.6792 | 1.4 | 1225 | 0.6564 | 0.0001 |
0.6849 | 1.42 | 1250 | 0.6558 | 0.0001 |
0.6856 | 1.45 | 1275 | 0.6556 | 0.0001 |
0.6856 | 1.48 | 1300 | 0.6551 | 0.0001 |
0.6856 | 1.51 | 1325 | 0.6550 | 0.0001 |
0.6857 | 1.54 | 1350 | 0.6543 | 0.0001 |
0.6856 | 1.57 | 1375 | 0.6539 | 0.0001 |
0.689 | 1.59 | 1400 | 0.6538 | 0.0001 |
0.6892 | 1.62 | 1425 | 0.6534 | 0.0001 |
0.6823 | 1.65 | 1450 | 0.6532 | 0.0001 |
0.6828 | 1.68 | 1475 | 0.6529 | 0.0001 |
0.6864 | 1.71 | 1500 | 0.6528 | 0.0001 |
0.6886 | 1.74 | 1525 | 0.6523 | 0.0001 |
0.6642 | 1.77 | 1550 | 0.6521 | 0.0001 |
0.6849 | 1.79 | 1575 | 0.6519 | 0.0001 |
0.6834 | 1.82 | 1600 | 0.6516 | 0.0001 |
0.6839 | 1.85 | 1625 | 0.6515 | 0.0001 |
0.6856 | 1.88 | 1650 | 0.6514 | 0.0001 |
0.6725 | 1.91 | 1675 | 0.6511 | 0.0001 |
0.6813 | 1.94 | 1700 | 0.6509 | 0.0001 |
0.6832 | 1.97 | 1725 | 0.6508 | 0.0001 |
0.6739 | 1.99 | 1750 | 0.6508 | 0.0001 |
0.6716 | 2.02 | 1775 | 0.6506 | 0.0001 |
0.6798 | 2.05 | 1800 | 0.6505 | 0.0001 |
0.6758 | 2.08 | 1825 | 0.6503 | 0.0001 |
0.6791 | 2.11 | 1850 | 0.6503 | 0.0001 |
0.6735 | 2.14 | 1875 | 0.6503 | 0.0001 |
0.6887 | 2.16 | 1900 | 0.6502 | 0.0001 |
0.686 | 2.19 | 1925 | 0.6502 | 0.0001 |
0.682 | 2.22 | 1950 | 0.6501 | 0.0001 |
0.675 | 2.25 | 1975 | 0.6501 | 0.0001 |
0.6792 | 2.28 | 2000 | 0.6501 | 0.0001 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.0.0+cu118
- Datasets 2.16.1
- Tokenizers 0.15.1
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