|
--- |
|
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 |
|
|
