|
--- |
|
license: apache-2.0 |
|
base_model: google/flan-t5-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: flan-t5-base-gsm8k_model |
|
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-base-gsm8k_model |
|
|
|
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: 0.8620 |
|
- Rouge1: 0.2697 |
|
- Rouge2: 0.1356 |
|
- Rougel: 0.2253 |
|
- Rougelsum: 0.2422 |
|
|
|
## 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: 0.0005 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
|
| 1.1948 | 1.0 | 654 | 0.9260 | 0.2684 | 0.1280 | 0.2208 | 0.2394 | |
|
| 0.9443 | 2.0 | 1308 | 0.8731 | 0.2686 | 0.1332 | 0.2242 | 0.2419 | |
|
| 0.8297 | 3.0 | 1962 | 0.8620 | 0.2697 | 0.1356 | 0.2253 | 0.2422 | |
|
| 0.6273 | 4.0 | 2616 | 0.8873 | 0.2732 | 0.1404 | 0.2289 | 0.2461 | |
|
| 0.558 | 5.0 | 3270 | 0.8902 | 0.2736 | 0.1426 | 0.2300 | 0.2464 | |
|
| 0.499 | 6.0 | 3924 | 0.9316 | 0.2750 | 0.1424 | 0.2305 | 0.2479 | |
|
| 0.4007 | 7.0 | 4578 | 0.9573 | 0.2777 | 0.1437 | 0.2322 | 0.2489 | |
|
| 0.353 | 8.0 | 5232 | 1.0082 | 0.2743 | 0.1431 | 0.2308 | 0.2478 | |
|
| 0.3235 | 9.0 | 5886 | 1.0506 | 0.2761 | 0.1463 | 0.2332 | 0.2499 | |
|
| 0.2644 | 10.0 | 6540 | 1.1053 | 0.2780 | 0.1465 | 0.2338 | 0.2509 | |
|
| 0.2325 | 11.0 | 7194 | 1.1463 | 0.2785 | 0.1478 | 0.2345 | 0.2513 | |
|
| 0.2171 | 12.0 | 7848 | 1.2101 | 0.2784 | 0.1492 | 0.2344 | 0.2518 | |
|
| 0.1852 | 13.0 | 8502 | 1.2566 | 0.2784 | 0.1470 | 0.2336 | 0.2506 | |
|
| 0.1692 | 14.0 | 9156 | 1.3192 | 0.2777 | 0.1463 | 0.2325 | 0.2498 | |
|
| 0.1602 | 15.0 | 9810 | 1.3562 | 0.2787 | 0.1473 | 0.2333 | 0.2507 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.1 |
|
|
