| | --- |
| | 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-muhammad |
| | 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-muhammad |
| |
|
| | 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: 0.0000 |
| | - Rouge1: 0.9614 |
| | - Rouge2: 0.6993 |
| | - Rougel: 0.9620 |
| | - Rougelsum: 0.9608 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | | 5.302 | 1.0 | 50 | 2.5839 | 0.0277 | 0.0 | 0.0266 | 0.0267 | |
| | | 2.806 | 2.0 | 100 | 1.6441 | 0.0944 | 0.0367 | 0.0940 | 0.0952 | |
| | | 1.3348 | 3.0 | 150 | 1.1077 | 0.1653 | 0.0429 | 0.1644 | 0.1650 | |
| | | 1.7996 | 4.0 | 200 | 0.7027 | 0.2908 | 0.1621 | 0.2864 | 0.2898 | |
| | | 0.7975 | 5.0 | 250 | 0.4608 | 0.4016 | 0.2158 | 0.3954 | 0.3971 | |
| | | 0.3679 | 6.0 | 300 | 0.3462 | 0.4970 | 0.2975 | 0.4969 | 0.5016 | |
| | | 0.8118 | 7.0 | 350 | 0.2211 | 0.6163 | 0.3819 | 0.6142 | 0.6161 | |
| | | 0.4616 | 8.0 | 400 | 0.1314 | 0.7334 | 0.4850 | 0.7321 | 0.7343 | |
| | | 0.4839 | 9.0 | 450 | 0.0681 | 0.8123 | 0.5500 | 0.8126 | 0.8130 | |
| | | 0.0311 | 10.0 | 500 | 0.0677 | 0.8569 | 0.5984 | 0.8564 | 0.8554 | |
| | | 0.4817 | 11.0 | 550 | 0.0445 | 0.8553 | 0.6003 | 0.8552 | 0.8563 | |
| | | 0.3256 | 12.0 | 600 | 0.0502 | 0.8970 | 0.6382 | 0.8964 | 0.8972 | |
| | | 0.2595 | 13.0 | 650 | 0.0243 | 0.9115 | 0.6440 | 0.9110 | 0.9110 | |
| | | 0.0417 | 14.0 | 700 | 0.0209 | 0.9417 | 0.6744 | 0.9407 | 0.9414 | |
| | | 0.0356 | 15.0 | 750 | 0.0110 | 0.9467 | 0.6840 | 0.9468 | 0.9449 | |
| | | 0.0033 | 16.0 | 800 | 0.0131 | 0.9426 | 0.6752 | 0.9423 | 0.9407 | |
| | | 0.0912 | 17.0 | 850 | 0.0043 | 0.9574 | 0.6933 | 0.9574 | 0.9564 | |
| | | 0.1195 | 18.0 | 900 | 0.0031 | 0.9608 | 0.6986 | 0.9613 | 0.9602 | |
| | | 0.0067 | 19.0 | 950 | 0.0026 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| | | 0.1854 | 20.0 | 1000 | 0.0017 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| | | 0.0199 | 21.0 | 1050 | 0.0017 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| | | 0.0022 | 22.0 | 1100 | 0.0006 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| | | 0.0014 | 23.0 | 1150 | 0.0005 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| | | 0.0823 | 24.0 | 1200 | 0.0002 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| | | 0.0012 | 25.0 | 1250 | 0.0002 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| | | 0.065 | 26.0 | 1300 | 0.0001 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| | | 0.0025 | 27.0 | 1350 | 0.0001 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| | | 0.0046 | 28.0 | 1400 | 0.0000 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| | | 0.004 | 29.0 | 1450 | 0.0000 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| | | 0.0011 | 30.0 | 1500 | 0.0000 | 0.9614 | 0.6993 | 0.9620 | 0.9608 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.45.2 |
| | - Pytorch 2.5.0+cu121 |
| | - Datasets 3.0.2 |
| | - Tokenizers 0.20.1 |
| |
|
