| --- |
| license: apache-2.0 |
| base_model: google/flan-t5-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: AI_Chaperone |
| 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. --> |
|
|
| # AI_Chaperone |
| |
| 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: 1.3785 |
| - Rouge1: 0.1505 |
| - Rouge2: 0.0376 |
| - Rougel: 0.1461 |
| - Rougelsum: 0.1475 |
| |
| ## 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: 8 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | No log | 1.0 | 380 | 0.8274 | 0.1131 | 0.0226 | 0.1105 | 0.1109 | |
| | 1.2345 | 2.0 | 760 | 0.8217 | 0.1146 | 0.0229 | 0.1124 | 0.1133 | |
| | 0.6137 | 3.0 | 1140 | 0.8487 | 0.1316 | 0.0277 | 0.1260 | 0.1277 | |
| | 0.4624 | 4.0 | 1520 | 0.9179 | 0.1382 | 0.0286 | 0.1333 | 0.1343 | |
| | 0.4624 | 5.0 | 1900 | 0.9816 | 0.1430 | 0.0288 | 0.1371 | 0.1391 | |
| | 0.3444 | 6.0 | 2280 | 1.0601 | 0.1545 | 0.0362 | 0.1510 | 0.1517 | |
| | 0.2751 | 7.0 | 2660 | 1.1619 | 0.1520 | 0.0335 | 0.1481 | 0.1483 | |
| | 0.2223 | 8.0 | 3040 | 1.2493 | 0.1515 | 0.0349 | 0.1472 | 0.1475 | |
| | 0.2223 | 9.0 | 3420 | 1.3379 | 0.1500 | 0.0381 | 0.1451 | 0.1464 | |
| | 0.1844 | 10.0 | 3800 | 1.3785 | 0.1505 | 0.0376 | 0.1461 | 0.1475 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.33.3 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
| |
