JuliusFx/dyu-fr-t5-base_v1
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: 1.3233
- Validation Loss: 3.0376
- Epoch: 46
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 |
---|---|---|
3.2963 | 3.1402 | 0 |
3.0454 | 3.0436 | 1 |
2.9282 | 3.0219 | 2 |
2.8338 | 2.9804 | 3 |
2.7463 | 2.9778 | 4 |
2.6807 | 2.9307 | 5 |
2.6156 | 2.9288 | 6 |
2.5501 | 2.9221 | 7 |
2.4933 | 2.9245 | 8 |
2.4400 | 2.9083 | 9 |
2.3910 | 2.9285 | 10 |
2.3451 | 2.9178 | 11 |
2.2967 | 2.9217 | 12 |
2.2496 | 2.9160 | 13 |
2.2099 | 2.9176 | 14 |
2.1726 | 2.8832 | 15 |
2.1317 | 2.9009 | 16 |
2.0931 | 2.8764 | 17 |
2.0541 | 2.8484 | 18 |
2.0237 | 2.8875 | 19 |
1.9935 | 2.8943 | 20 |
1.9538 | 2.8810 | 21 |
1.9218 | 2.8885 | 22 |
1.8905 | 2.8650 | 23 |
1.8631 | 2.8671 | 24 |
1.8290 | 2.8832 | 25 |
1.8046 | 2.8879 | 26 |
1.7761 | 2.9429 | 27 |
1.7414 | 2.9406 | 28 |
1.7167 | 2.9296 | 29 |
1.6926 | 2.9174 | 30 |
1.6639 | 2.9762 | 31 |
1.6421 | 2.9700 | 32 |
1.6102 | 2.9565 | 33 |
1.5877 | 2.9810 | 34 |
1.5658 | 2.9643 | 35 |
1.5390 | 3.0225 | 36 |
1.5152 | 3.0029 | 37 |
1.4990 | 2.9756 | 38 |
1.4748 | 3.0228 | 39 |
1.4483 | 3.0092 | 40 |
1.4286 | 3.0356 | 41 |
1.4051 | 3.0226 | 42 |
1.3841 | 3.0442 | 43 |
1.3577 | 3.0595 | 44 |
1.3433 | 3.0547 | 45 |
1.3233 | 3.0376 | 46 |
Framework versions
- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for JuliusFx/dyu-fr-t5-base_v1
Base model
google-t5/t5-base