File size: 4,211 Bytes
6c9de47 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 | ---
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ft5-rouge-durga-q1-clean
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ft5-rouge-durga-q1-clean
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2757
- Rouge1: 0.5561
- Rouge2: 0.4369
- Rougel: 0.5537
- Rougelsum: 0.5562
## 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: 0.0003
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.0328 | 1.0 | 3 | 2.0694 | 0.2530 | 0.0656 | 0.2481 | 0.2492 |
| 1.8606 | 2.0 | 6 | 1.8619 | 0.3034 | 0.1007 | 0.2997 | 0.2986 |
| 2.8564 | 3.0 | 9 | 1.6705 | 0.2502 | 0.0631 | 0.2503 | 0.2506 |
| 1.4505 | 4.0 | 12 | 1.5098 | 0.2678 | 0.0531 | 0.2643 | 0.2645 |
| 1.5253 | 5.0 | 15 | 1.3533 | 0.3090 | 0.0953 | 0.3001 | 0.2987 |
| 1.9042 | 6.0 | 18 | 1.2238 | 0.3606 | 0.1385 | 0.3513 | 0.3500 |
| 1.7751 | 7.0 | 21 | 1.1186 | 0.3858 | 0.1532 | 0.3798 | 0.3777 |
| 1.1806 | 8.0 | 24 | 1.0301 | 0.3814 | 0.1448 | 0.3781 | 0.3763 |
| 1.0575 | 9.0 | 27 | 0.9449 | 0.4090 | 0.1835 | 0.4052 | 0.4038 |
| 0.9038 | 10.0 | 30 | 0.8609 | 0.4062 | 0.1918 | 0.4029 | 0.4021 |
| 1.4179 | 11.0 | 33 | 0.7875 | 0.4190 | 0.1933 | 0.4150 | 0.4149 |
| 1.435 | 12.0 | 36 | 0.7099 | 0.4075 | 0.1938 | 0.4047 | 0.4040 |
| 0.6608 | 13.0 | 39 | 0.6601 | 0.4206 | 0.2241 | 0.4188 | 0.4177 |
| 0.4501 | 14.0 | 42 | 0.6165 | 0.4445 | 0.2389 | 0.4380 | 0.4369 |
| 0.5584 | 15.0 | 45 | 0.5831 | 0.4465 | 0.2435 | 0.4472 | 0.4448 |
| 1.1468 | 16.0 | 48 | 0.5449 | 0.4461 | 0.2476 | 0.4452 | 0.4427 |
| 0.5354 | 17.0 | 51 | 0.5032 | 0.4260 | 0.2328 | 0.4276 | 0.4274 |
| 0.8386 | 18.0 | 54 | 0.4703 | 0.4049 | 0.2191 | 0.4041 | 0.4050 |
| 0.7596 | 19.0 | 57 | 0.4393 | 0.4272 | 0.2495 | 0.4267 | 0.4298 |
| 0.9838 | 20.0 | 60 | 0.4084 | 0.4517 | 0.2788 | 0.4517 | 0.4520 |
| 1.0146 | 21.0 | 63 | 0.3784 | 0.4578 | 0.2803 | 0.4576 | 0.4565 |
| 0.6939 | 22.0 | 66 | 0.3560 | 0.4934 | 0.3226 | 0.4963 | 0.4932 |
| 0.7661 | 23.0 | 69 | 0.3385 | 0.4949 | 0.3303 | 0.4972 | 0.4960 |
| 0.9235 | 24.0 | 72 | 0.3231 | 0.5357 | 0.4006 | 0.5362 | 0.5375 |
| 0.5005 | 25.0 | 75 | 0.3099 | 0.5466 | 0.4179 | 0.5466 | 0.5465 |
| 0.382 | 26.0 | 78 | 0.2982 | 0.5542 | 0.4330 | 0.5534 | 0.5546 |
| 0.5445 | 27.0 | 81 | 0.2882 | 0.5688 | 0.4555 | 0.5684 | 0.5673 |
| 0.5974 | 28.0 | 84 | 0.2816 | 0.5688 | 0.4555 | 0.5684 | 0.5673 |
| 0.6571 | 29.0 | 87 | 0.2775 | 0.5561 | 0.4369 | 0.5537 | 0.5562 |
| 0.5589 | 30.0 | 90 | 0.2757 | 0.5561 | 0.4369 | 0.5537 | 0.5562 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1
|