<!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. -->
cewinharhar/iceCream
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 1.1909
- Validation Loss: 3.0925
- Epoch: 92
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': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
Train Loss | Validation Loss | Epoch |
---|---|---|
4.9926 | 4.0419 | 0 |
3.9831 | 3.8247 | 1 |
3.8396 | 3.7337 | 2 |
3.7352 | 3.6509 | 3 |
3.6382 | 3.5948 | 4 |
3.5595 | 3.5458 | 5 |
3.4845 | 3.4667 | 6 |
3.4140 | 3.4460 | 7 |
3.3546 | 3.4035 | 8 |
3.2939 | 3.3571 | 9 |
3.2420 | 3.3465 | 10 |
3.1867 | 3.2970 | 11 |
3.1418 | 3.2716 | 12 |
3.0865 | 3.2609 | 13 |
3.0419 | 3.2318 | 14 |
2.9962 | 3.2279 | 15 |
2.9551 | 3.1991 | 16 |
2.9178 | 3.1656 | 17 |
2.8701 | 3.1654 | 18 |
2.8348 | 3.1372 | 19 |
2.7988 | 3.1281 | 20 |
2.7597 | 3.0978 | 21 |
2.7216 | 3.1019 | 22 |
2.6844 | 3.0388 | 23 |
2.6489 | 3.0791 | 24 |
2.6192 | 3.0885 | 25 |
2.5677 | 3.0388 | 26 |
2.5478 | 3.0530 | 27 |
2.5136 | 3.0403 | 28 |
2.4756 | 3.0521 | 29 |
2.4454 | 3.0173 | 30 |
2.4203 | 3.0079 | 31 |
2.3882 | 3.0325 | 32 |
2.3596 | 3.0066 | 33 |
2.3279 | 2.9919 | 34 |
2.2947 | 2.9871 | 35 |
2.2712 | 2.9834 | 36 |
2.2311 | 2.9917 | 37 |
2.2022 | 2.9796 | 38 |
2.1703 | 2.9641 | 39 |
2.1394 | 2.9571 | 40 |
2.1237 | 2.9662 | 41 |
2.0949 | 2.9358 | 42 |
2.0673 | 2.9653 | 43 |
2.0417 | 2.9416 | 44 |
2.0194 | 2.9531 | 45 |
2.0009 | 2.9417 | 46 |
1.9716 | 2.9325 | 47 |
1.9488 | 2.9476 | 48 |
1.9265 | 2.9559 | 49 |
1.8975 | 2.9477 | 50 |
1.8815 | 2.9429 | 51 |
1.8552 | 2.9119 | 52 |
1.8358 | 2.9377 | 53 |
1.8226 | 2.9605 | 54 |
1.7976 | 2.9446 | 55 |
1.7677 | 2.9162 | 56 |
1.7538 | 2.9292 | 57 |
1.7376 | 2.9968 | 58 |
1.7156 | 2.9525 | 59 |
1.7001 | 2.9275 | 60 |
1.6806 | 2.9714 | 61 |
1.6582 | 2.9903 | 62 |
1.6436 | 2.9363 | 63 |
1.6254 | 2.9714 | 64 |
1.6093 | 2.9804 | 65 |
1.5900 | 2.9740 | 66 |
1.5686 | 2.9835 | 67 |
1.5492 | 3.0018 | 68 |
1.5371 | 3.0088 | 69 |
1.5245 | 2.9780 | 70 |
1.5021 | 3.0176 | 71 |
1.4839 | 2.9917 | 72 |
1.4726 | 3.0602 | 73 |
1.4568 | 3.0055 | 74 |
1.4435 | 3.0186 | 75 |
1.4225 | 2.9948 | 76 |
1.4088 | 3.0270 | 77 |
1.3947 | 3.0676 | 78 |
1.3780 | 3.0615 | 79 |
1.3627 | 3.0780 | 80 |
1.3445 | 3.0491 | 81 |
1.3293 | 3.0534 | 82 |
1.3130 | 3.0460 | 83 |
1.2980 | 3.0846 | 84 |
1.2895 | 3.0709 | 85 |
1.2737 | 3.0903 | 86 |
1.2557 | 3.0854 | 87 |
1.2499 | 3.1101 | 88 |
1.2353 | 3.1181 | 89 |
1.2104 | 3.1111 | 90 |
1.2101 | 3.1153 | 91 |
1.1909 | 3.0925 | 92 |
Framework versions
- Transformers 4.19.2
- TensorFlow 2.9.1
- Datasets 2.1.0
- Tokenizers 0.12.1