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ghdi/punic-model

This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 3.9858
  • Validation Loss: 7.6193
  • Epoch: 59

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:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 5e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': -984, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: mixed_float16

Training results

Train Loss Validation Loss Epoch
10.9100 10.8188 0
10.7129 10.4690 1
10.3775 10.1048 2
10.0587 9.8271 3
9.8034 9.6395 4
9.6209 9.5085 5
9.5047 9.4043 6
9.3724 9.3072 7
9.2873 9.2090 8
9.1690 9.1091 9
8.9963 9.0013 10
8.8724 8.8875 11
8.7316 8.7701 12
8.6070 8.6477 13
8.4242 8.5243 14
8.2700 8.4018 15
8.1555 8.2834 16
7.9978 8.1696 17
7.8495 8.0607 18
7.6980 7.9635 19
7.5339 7.8726 20
7.4741 7.7917 21
7.3669 7.7233 22
7.2598 7.6604 23
7.1434 7.6088 24
7.0434 7.5579 25
6.9874 7.5171 26
6.8629 7.4881 27
6.8293 7.4694 28
6.6349 7.4367 29
6.7589 7.4071 30
6.5890 7.4003 31
6.5476 7.3576 32
6.4606 7.3400 33
6.3945 7.3327 34
6.2495 7.3435 35
6.0722 7.3375 36
6.1324 7.3365 37
6.0493 7.3458 38
5.9514 7.4002 39
5.8638 7.3356 40
5.7390 7.3488 41
5.6403 7.3687 42
5.5442 7.3831 43
5.4542 7.3888 44
5.3243 7.4340 45
5.2295 7.4170 46
5.1436 7.4110 47
5.0199 7.5223 48
4.9058 7.5142 49
4.8393 7.4926 50
4.7104 7.5253 51
4.6212 7.5420 52
4.5298 7.5799 53
4.4251 7.5940 54
4.3130 7.5752 55
4.2240 7.6315 56
4.1587 7.6412 57
4.0442 7.6748 58
3.9858 7.6193 59

Framework versions

  • Transformers 4.28.1
  • TensorFlow 2.12.0
  • Datasets 2.11.0
  • Tokenizers 0.13.3
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