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flan-t5-base-model2
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: 0.2236
- Rouge1: 73.2746
- Rouge2: 65.1173
- Rougel: 72.149
- Rougelsum: 73.1838
- Gen Len: 16.1625
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 11.4224 | 0.71 | 200 | 0.5002 | 49.2994 | 40.066 | 49.0355 | 49.3658 | 7.6113 |
| 0.4129 | 1.41 | 400 | 0.3030 | 72.7746 | 63.8666 | 71.4539 | 72.5604 | 16.2138 |
| 0.3131 | 2.12 | 600 | 0.2793 | 73.6239 | 64.6532 | 72.2694 | 73.5208 | 16.1148 |
| 0.2615 | 2.83 | 800 | 0.2674 | 73.2672 | 64.6251 | 72.0459 | 73.0736 | 16.2067 |
| 0.2347 | 3.53 | 1000 | 0.2631 | 73.0069 | 64.3272 | 71.8482 | 72.963 | 16.2049 |
| 0.2222 | 4.24 | 1200 | 0.2437 | 73.3821 | 64.9656 | 72.1995 | 73.2511 | 16.0795 |
| 0.2077 | 4.95 | 1400 | 0.2450 | 73.1663 | 64.7168 | 72.023 | 73.0977 | 16.0936 |
| 0.1976 | 5.65 | 1600 | 0.2296 | 73.2977 | 64.8011 | 72.2179 | 73.3089 | 16.1661 |
| 0.1804 | 6.36 | 1800 | 0.2268 | 73.1599 | 64.852 | 72.0518 | 73.1532 | 16.1802 |
| 0.1842 | 7.07 | 2000 | 0.2284 | 73.2343 | 64.944 | 72.046 | 73.1038 | 16.159 |
| 0.1776 | 7.77 | 2200 | 0.2255 | 73.3332 | 65.119 | 72.1684 | 73.2489 | 16.1449 |
| 0.1621 | 8.48 | 2400 | 0.2231 | 73.2057 | 64.9477 | 72.1727 | 73.1358 | 16.1219 |
| 0.1657 | 9.19 | 2600 | 0.2234 | 73.2285 | 65.0575 | 72.0227 | 73.2392 | 16.1608 |
| 0.1653 | 9.89 | 2800 | 0.2236 | 73.2746 | 65.1173 | 72.149 | 73.1838 | 16.1625 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
