|
|
--- |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- summarization |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: mt5-small-text-sum-6 |
|
|
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. --> |
|
|
|
|
|
# mt5-small-text-sum-6 |
|
|
|
|
|
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 2.3694 |
|
|
- Rouge1: 20.18 |
|
|
- Rouge2: 6.52 |
|
|
- Rougel: 19.84 |
|
|
|
|
|
## 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: 0.0001 |
|
|
- train_batch_size: 12 |
|
|
- eval_batch_size: 12 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 40 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:| |
|
|
| 4.4337 | 1.93 | 500 | 2.5989 | 15.94 | 4.85 | 15.78 | |
|
|
| 3.0621 | 3.86 | 1000 | 2.4750 | 19.09 | 5.95 | 18.82 | |
|
|
| 2.8411 | 5.79 | 1500 | 2.4011 | 18.39 | 5.69 | 18.22 | |
|
|
| 2.6947 | 7.72 | 2000 | 2.3851 | 19.27 | 5.79 | 19.01 | |
|
|
| 2.5872 | 9.65 | 2500 | 2.3918 | 19.09 | 6.02 | 18.81 | |
|
|
| 2.4996 | 11.58 | 3000 | 2.3689 | 18.84 | 5.84 | 18.46 | |
|
|
| 2.4192 | 13.51 | 3500 | 2.3604 | 19.89 | 5.97 | 19.5 | |
|
|
| 2.3524 | 15.44 | 4000 | 2.3694 | 20.18 | 6.52 | 19.84 | |
|
|
| 2.3012 | 17.37 | 4500 | 2.3637 | 19.24 | 5.51 | 18.9 | |
|
|
| 2.2408 | 19.31 | 5000 | 2.3374 | 19.78 | 6.27 | 19.43 | |
|
|
| 2.2004 | 21.24 | 5500 | 2.3400 | 19.74 | 6.06 | 19.37 | |
|
|
| 2.1631 | 23.17 | 6000 | 2.3584 | 19.95 | 6.08 | 19.53 | |
|
|
| 2.123 | 25.1 | 6500 | 2.3527 | 19.64 | 5.9 | 19.36 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.26.1 |
|
|
- Pytorch 1.13.1+cu116 |
|
|
- Datasets 2.10.1 |
|
|
- Tokenizers 0.13.2 |
|
|
|
