metadata
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: flan_t5_base_patent
results: []
flan_t5_base_patent
This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9077
- Accuracy: 0.6922
- F1 Macro: 0.6251
- F1 Micro: 0.6922
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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|---|---|---|---|---|---|---|
| 1.3252 | 0.06 | 50 | 1.3453 | 0.5512 | 0.4078 | 0.5512 |
| 1.1367 | 0.13 | 100 | 1.1291 | 0.613 | 0.4903 | 0.613 |
| 1.1672 | 0.19 | 150 | 1.0973 | 0.6288 | 0.5119 | 0.6288 |
| 1.0094 | 0.26 | 200 | 1.0517 | 0.6368 | 0.5609 | 0.6368 |
| 0.9798 | 0.32 | 250 | 1.0432 | 0.6466 | 0.5584 | 0.6466 |
| 1.1403 | 0.38 | 300 | 1.0146 | 0.6542 | 0.5733 | 0.6542 |
| 1.0617 | 0.45 | 350 | 1.0112 | 0.652 | 0.5857 | 0.652 |
| 0.9333 | 0.51 | 400 | 1.0339 | 0.6436 | 0.5698 | 0.6436 |
| 1.0316 | 0.58 | 450 | 0.9973 | 0.6622 | 0.5891 | 0.6622 |
| 0.9675 | 0.64 | 500 | 0.9732 | 0.6698 | 0.6110 | 0.6698 |
| 0.9452 | 0.7 | 550 | 0.9900 | 0.6652 | 0.5890 | 0.6652 |
| 1.0378 | 0.77 | 600 | 0.9751 | 0.668 | 0.6075 | 0.668 |
| 1.0038 | 0.83 | 650 | 0.9483 | 0.67 | 0.6076 | 0.67 |
| 0.9509 | 0.9 | 700 | 0.9739 | 0.6614 | 0.6000 | 0.6614 |
| 0.9378 | 0.96 | 750 | 0.9684 | 0.6686 | 0.5962 | 0.6686 |
| 0.801 | 1.02 | 800 | 0.9589 | 0.6696 | 0.6145 | 0.6696 |
| 0.7911 | 1.09 | 850 | 0.9881 | 0.6606 | 0.5857 | 0.6606 |
| 0.8237 | 1.15 | 900 | 0.9677 | 0.6728 | 0.6116 | 0.6728 |
| 0.828 | 1.21 | 950 | 0.9609 | 0.6708 | 0.6069 | 0.6708 |
| 0.8477 | 1.28 | 1000 | 0.9733 | 0.663 | 0.6126 | 0.663 |
| 0.6792 | 1.34 | 1050 | 0.9752 | 0.6804 | 0.6096 | 0.6804 |
| 0.7903 | 1.41 | 1100 | 0.9644 | 0.6778 | 0.6199 | 0.6778 |
| 0.8033 | 1.47 | 1150 | 0.9827 | 0.663 | 0.6004 | 0.663 |
| 0.7558 | 1.53 | 1200 | 0.9423 | 0.6886 | 0.6196 | 0.6886 |
| 0.767 | 1.6 | 1250 | 0.9510 | 0.6762 | 0.6269 | 0.6762 |
| 0.7842 | 1.66 | 1300 | 0.9351 | 0.689 | 0.6307 | 0.689 |
| 0.8388 | 1.73 | 1350 | 0.9174 | 0.6934 | 0.6275 | 0.6934 |
| 0.7356 | 1.79 | 1400 | 0.9241 | 0.6914 | 0.6327 | 0.6914 |
| 0.6714 | 1.85 | 1450 | 0.9077 | 0.6922 | 0.6251 | 0.6922 |
| 0.9696 | 1.92 | 1500 | 0.9081 | 0.6884 | 0.6169 | 0.6884 |
| 0.7278 | 1.98 | 1550 | 0.9106 | 0.6888 | 0.6269 | 0.6888 |
| 0.5103 | 2.05 | 1600 | 0.9648 | 0.6934 | 0.6278 | 0.6934 |
| 0.4725 | 2.11 | 1650 | 0.9807 | 0.687 | 0.6287 | 0.687 |
| 0.643 | 2.17 | 1700 | 0.9953 | 0.6912 | 0.6252 | 0.6912 |
| 0.5967 | 2.24 | 1750 | 0.9662 | 0.6868 | 0.6326 | 0.6868 |
| 0.5582 | 2.3 | 1800 | 0.9957 | 0.6896 | 0.6307 | 0.6896 |
| 0.5341 | 2.37 | 1850 | 1.0167 | 0.69 | 0.6324 | 0.69 |
| 0.494 | 2.43 | 1900 | 1.0182 | 0.6884 | 0.6304 | 0.6884 |
| 0.4602 | 2.49 | 1950 | 1.0200 | 0.6908 | 0.6376 | 0.6908 |
| 0.5453 | 2.56 | 2000 | 1.0206 | 0.692 | 0.6426 | 0.692 |
| 0.5462 | 2.62 | 2050 | 1.0130 | 0.6904 | 0.6392 | 0.6904 |
| 0.4283 | 2.69 | 2100 | 1.0353 | 0.6866 | 0.6374 | 0.6866 |
| 0.5238 | 2.75 | 2150 | 1.0244 | 0.691 | 0.6418 | 0.691 |
| 0.5237 | 2.81 | 2200 | 1.0162 | 0.6904 | 0.6388 | 0.6904 |
| 0.6074 | 2.88 | 2250 | 1.0166 | 0.6938 | 0.6458 | 0.6938 |
| 0.5846 | 2.94 | 2300 | 1.0134 | 0.6936 | 0.6454 | 0.6936 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2