|
--- |
|
license: apache-2.0 |
|
base_model: google/flan-t5-small |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: flan-t5-small-test |
|
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-small-test |
|
|
|
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4375 |
|
- Rouge1: 55.6701 |
|
- Rouge2: 45.6817 |
|
- Rougel: 52.259 |
|
- Rougelsum: 52.2632 |
|
- Gen Len: 494.295 |
|
|
|
## 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: 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: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
| No log | 1.0 | 100 | 0.4736 | 47.5356 | 37.7662 | 43.8872 | 43.933 | 493.725 | |
|
| No log | 2.0 | 200 | 0.4582 | 51.7559 | 41.8487 | 48.1235 | 48.1762 | 494.835 | |
|
| No log | 3.0 | 300 | 0.4469 | 52.8576 | 43.1039 | 49.3153 | 49.36 | 493.225 | |
|
| No log | 4.0 | 400 | 0.4395 | 55.4214 | 45.3968 | 51.8613 | 51.8725 | 492.5 | |
|
| 0.5066 | 5.0 | 500 | 0.4375 | 55.6701 | 45.6817 | 52.259 | 52.2632 | 494.295 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.1 |
|
|
