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library_name: transformers
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-rouge-durga-3
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. -->
# flan-t5-rouge-durga-3
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0024
- Rouge1: 0.5907
- Rouge2: 0.5623
- Rougel: 0.5912
- Rougelsum: 0.5922
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.4258 | 1.0 | 50 | 2.0073 | 0.2733 | 0.1044 | 0.2514 | 0.2517 |
| 2.2156 | 2.0 | 100 | 1.5972 | 0.2600 | 0.0904 | 0.2466 | 0.2473 |
| 1.9538 | 3.0 | 150 | 1.2838 | 0.2999 | 0.1401 | 0.2867 | 0.2877 |
| 1.2774 | 4.0 | 200 | 1.0377 | 0.3370 | 0.1809 | 0.3253 | 0.3273 |
| 1.2395 | 5.0 | 250 | 0.8060 | 0.3688 | 0.2162 | 0.3561 | 0.3589 |
| 1.6069 | 6.0 | 300 | 0.6646 | 0.3898 | 0.2558 | 0.3752 | 0.3774 |
| 1.2469 | 7.0 | 350 | 0.5189 | 0.4014 | 0.2612 | 0.3875 | 0.3896 |
| 0.664 | 8.0 | 400 | 0.4060 | 0.4506 | 0.3294 | 0.4380 | 0.4402 |
| 1.8862 | 9.0 | 450 | 0.3131 | 0.4657 | 0.3734 | 0.4600 | 0.4623 |
| 0.3403 | 10.0 | 500 | 0.2534 | 0.4662 | 0.3662 | 0.4602 | 0.4622 |
| 0.5261 | 11.0 | 550 | 0.1996 | 0.4984 | 0.4243 | 0.4951 | 0.4967 |
| 1.0378 | 12.0 | 600 | 0.1467 | 0.5047 | 0.4431 | 0.5035 | 0.5055 |
| 0.218 | 13.0 | 650 | 0.1176 | 0.4912 | 0.4286 | 0.4883 | 0.4924 |
| 0.5121 | 14.0 | 700 | 0.0843 | 0.5418 | 0.4951 | 0.5416 | 0.5427 |
| 0.4996 | 15.0 | 750 | 0.0679 | 0.5645 | 0.5231 | 0.5612 | 0.5645 |
| 0.2511 | 16.0 | 800 | 0.0521 | 0.5426 | 0.4922 | 0.5399 | 0.5434 |
| 0.3803 | 17.0 | 850 | 0.0395 | 0.5607 | 0.5232 | 0.5604 | 0.5616 |
| 0.0706 | 18.0 | 900 | 0.0261 | 0.5816 | 0.5460 | 0.5824 | 0.5838 |
| 0.1628 | 19.0 | 950 | 0.0193 | 0.5833 | 0.5541 | 0.5843 | 0.5848 |
| 0.1777 | 20.0 | 1000 | 0.0141 | 0.5833 | 0.5524 | 0.5831 | 0.5853 |
| 0.1254 | 21.0 | 1050 | 0.0122 | 0.5849 | 0.5554 | 0.5842 | 0.5866 |
| 0.2481 | 22.0 | 1100 | 0.0109 | 0.5916 | 0.5616 | 0.5915 | 0.5932 |
| 0.0604 | 23.0 | 1150 | 0.0066 | 0.5912 | 0.5623 | 0.5909 | 0.5926 |
| 0.1083 | 24.0 | 1200 | 0.0048 | 0.5902 | 0.5611 | 0.5904 | 0.5916 |
| 0.2921 | 25.0 | 1250 | 0.0051 | 0.5890 | 0.5602 | 0.5891 | 0.5904 |
| 0.1846 | 26.0 | 1300 | 0.0037 | 0.5902 | 0.5618 | 0.5907 | 0.5920 |
| 0.1952 | 27.0 | 1350 | 0.0029 | 0.5907 | 0.5623 | 0.5912 | 0.5922 |
| 0.0419 | 28.0 | 1400 | 0.0026 | 0.5897 | 0.5611 | 0.5898 | 0.5914 |
| 0.1353 | 29.0 | 1450 | 0.0025 | 0.5906 | 0.5618 | 0.5902 | 0.5916 |
| 0.0072 | 30.0 | 1500 | 0.0024 | 0.5907 | 0.5623 | 0.5912 | 0.5922 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1
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