|
--- |
|
license: apache-2.0 |
|
base_model: google/flan-t5-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: flant5-base |
|
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. --> |
|
|
|
# flant5-base |
|
|
|
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: 0.2172 |
|
- Rouge1: 40.5681 |
|
- Rouge2: 19.3464 |
|
- Rougel: 35.9679 |
|
- Rougelsum: 37.6605 |
|
- Gen Len: 19.97 |
|
|
|
## 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: 3 |
|
- eval_batch_size: 3 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 3 |
|
- total_train_batch_size: 9 |
|
- 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 | Gen Len | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
| 0.293 | 1.0 | 1384 | 0.2280 | 38.7963 | 16.8581 | 33.5577 | 35.6059 | 19.96 | |
|
| 0.2515 | 2.0 | 2769 | 0.2203 | 38.8289 | 16.9039 | 33.5277 | 35.3638 | 19.982 | |
|
| 0.2347 | 3.0 | 4154 | 0.2155 | 39.8194 | 18.4008 | 34.6872 | 36.6037 | 19.968 | |
|
| 0.223 | 4.0 | 5538 | 0.2148 | 40.1964 | 18.4087 | 34.9626 | 36.8748 | 19.96 | |
|
| 0.2135 | 5.0 | 6923 | 0.2149 | 40.5411 | 19.0474 | 35.5895 | 37.4265 | 19.962 | |
|
| 0.2056 | 6.0 | 8308 | 0.2146 | 40.3302 | 19.1785 | 35.6352 | 37.4875 | 19.962 | |
|
| 0.1999 | 7.0 | 9692 | 0.2147 | 40.0187 | 19.143 | 35.3324 | 37.1204 | 19.958 | |
|
| 0.1948 | 8.0 | 11077 | 0.2159 | 40.1846 | 19.1643 | 35.7202 | 37.4115 | 19.966 | |
|
| 0.1915 | 9.0 | 12462 | 0.2169 | 40.7785 | 19.5846 | 36.1499 | 37.9102 | 19.96 | |
|
| 0.1888 | 10.0 | 13840 | 0.2172 | 40.5681 | 19.3464 | 35.9679 | 37.6605 | 19.97 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.1 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.15.2 |
|
|
