results
This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.6519
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 16
- training_steps: 1698
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.2568 | 0.59 | 50 | 2.9764 |
| 3.2186 | 1.18 | 100 | 2.9349 |
| 3.1884 | 1.76 | 150 | 2.8820 |
| 3.1448 | 2.35 | 200 | 2.8404 |
| 3.1166 | 2.94 | 250 | 2.8120 |
| 3.0742 | 3.53 | 300 | 2.7899 |
| 3.0662 | 4.12 | 350 | 2.7724 |
| 3.0379 | 4.71 | 400 | 2.7578 |
| 3.0301 | 5.29 | 450 | 2.7457 |
| 3.0071 | 5.88 | 500 | 2.7352 |
| 3.0084 | 6.47 | 550 | 2.7259 |
| 2.9632 | 7.06 | 600 | 2.7177 |
| 2.9706 | 7.65 | 650 | 2.7104 |
| 2.9543 | 8.24 | 700 | 2.7037 |
| 2.9573 | 8.82 | 750 | 2.6979 |
| 2.9663 | 9.41 | 800 | 2.6928 |
| 2.9243 | 10.0 | 850 | 2.6877 |
| 2.9451 | 10.59 | 900 | 2.6832 |
| 2.9027 | 11.18 | 950 | 2.6790 |
| 2.9255 | 11.76 | 1000 | 2.6754 |
| 2.916 | 12.35 | 1050 | 2.6719 |
| 2.9155 | 12.94 | 1100 | 2.6688 |
| 2.9223 | 13.53 | 1150 | 2.6659 |
| 2.9141 | 14.12 | 1200 | 2.6635 |
| 2.8931 | 14.71 | 1250 | 2.6612 |
| 2.8988 | 15.29 | 1300 | 2.6590 |
| 2.8986 | 15.88 | 1350 | 2.6573 |
| 2.8998 | 16.47 | 1400 | 2.6558 |
| 2.9004 | 17.06 | 1450 | 2.6546 |
| 2.9036 | 17.65 | 1500 | 2.6535 |
| 2.885 | 18.24 | 1550 | 2.6528 |
| 2.8994 | 18.82 | 1600 | 2.6522 |
| 2.8971 | 19.41 | 1650 | 2.6519 |
Framework versions
- PEFT 0.8.2
- Transformers 4.38.1
- Pytorch 2.3.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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Base model
google/flan-t5-base