metadata
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: flan-t5-base-samsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: test
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 47.08
flan-t5-base-samsum
This model is a fine-tuned version of google/flan-t5-base on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.3859
- Rouge1: 47.08
- Rouge2: 23.2603
- Rougel: 39.2645
- Rougelsum: 43.2898
- Gen Len: 17.3333
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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.5121 | 0.08 | 50 | 1.4287 | 46.7443 | 22.8826 | 38.9466 | 42.862 | 16.9634 |
| 1.46 | 0.16 | 100 | 1.4199 | 46.7723 | 22.8011 | 39.0224 | 42.9095 | 17.2393 |
| 1.4515 | 0.24 | 150 | 1.4147 | 46.6593 | 23.027 | 38.9378 | 42.8492 | 17.1245 |
| 1.4679 | 0.33 | 200 | 1.4121 | 46.8312 | 22.8345 | 39.1545 | 43.2035 | 17.3431 |
| 1.451 | 0.41 | 250 | 1.4109 | 46.826 | 23.038 | 39.2744 | 43.3106 | 17.2686 |
| 1.4434 | 0.49 | 300 | 1.4040 | 46.6744 | 23.0221 | 39.3167 | 43.1835 | 16.9158 |
| 1.4417 | 0.57 | 350 | 1.4007 | 46.851 | 23.0448 | 39.2346 | 43.2396 | 17.1172 |
| 1.4781 | 0.65 | 400 | 1.3952 | 46.7831 | 23.1146 | 39.295 | 43.2256 | 17.2076 |
| 1.4626 | 0.73 | 450 | 1.3940 | 47.0933 | 23.2741 | 39.2954 | 43.3102 | 17.2222 |
| 1.4307 | 0.81 | 500 | 1.3955 | 46.8827 | 23.2016 | 39.2817 | 43.2379 | 17.2002 |
| 1.4586 | 0.9 | 550 | 1.3933 | 46.7152 | 23.1439 | 39.2576 | 43.1754 | 17.3040 |
| 1.4465 | 0.98 | 600 | 1.3905 | 46.8332 | 23.3356 | 39.2596 | 43.2472 | 17.3468 |
| 1.381 | 1.06 | 650 | 1.3953 | 46.9289 | 22.9605 | 39.0651 | 43.2085 | 17.4066 |
| 1.4125 | 1.14 | 700 | 1.3922 | 46.4822 | 23.0893 | 38.9024 | 42.9789 | 17.2381 |
| 1.3667 | 1.22 | 750 | 1.3922 | 47.2977 | 23.4064 | 39.5091 | 43.5742 | 17.2930 |
| 1.3878 | 1.3 | 800 | 1.3953 | 46.6405 | 23.2132 | 39.2853 | 43.3049 | 17.3358 |
| 1.3884 | 1.38 | 850 | 1.3931 | 46.9152 | 23.1594 | 39.1629 | 43.2254 | 17.3614 |
| 1.3766 | 1.47 | 900 | 1.3898 | 46.988 | 23.1708 | 39.2446 | 43.311 | 17.3333 |
| 1.3727 | 1.55 | 950 | 1.3889 | 46.6771 | 23.0915 | 39.0787 | 43.0184 | 17.3211 |
| 1.4001 | 1.63 | 1000 | 1.3859 | 47.08 | 23.2603 | 39.2645 | 43.2898 | 17.3333 |
| 1.3894 | 1.71 | 1050 | 1.3874 | 47.2134 | 23.3696 | 39.4356 | 43.5422 | 17.3297 |
| 1.3697 | 1.79 | 1100 | 1.3860 | 47.06 | 23.3769 | 39.3494 | 43.4113 | 17.3504 |
| 1.3886 | 1.87 | 1150 | 1.3862 | 47.0159 | 23.3728 | 39.3871 | 43.4016 | 17.3260 |
| 1.4037 | 1.95 | 1200 | 1.3861 | 47.0039 | 23.4055 | 39.3356 | 43.3787 | 17.3321 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.0+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3