|
--- |
|
license: apache-2.0 |
|
base_model: google/mt5-small |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: mt5-small-finetuned-xlsum-en-zh |
|
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-finetuned-xlsum-en-zh |
|
|
|
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.2988 |
|
- Rouge1: 12.7272 |
|
- Rouge2: 2.4338 |
|
- Rougel: 10.5647 |
|
- Rougelsum: 10.5889 |
|
|
|
## 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: 5.6e-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: 8 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
|
| 6.215 | 1.0 | 1000 | 3.5021 | 10.9361 | 1.9845 | 9.1348 | 9.0929 | |
|
| 4.6051 | 2.0 | 2000 | 3.4190 | 11.6653 | 2.0884 | 9.6847 | 9.7251 | |
|
| 4.3735 | 3.0 | 3000 | 3.3685 | 12.1941 | 2.2109 | 10.2818 | 10.237 | |
|
| 4.2439 | 4.0 | 4000 | 3.3417 | 12.6308 | 2.4293 | 10.5036 | 10.5079 | |
|
| 4.1552 | 5.0 | 5000 | 3.3148 | 12.5122 | 2.2873 | 10.3496 | 10.3545 | |
|
| 4.0853 | 6.0 | 6000 | 3.3112 | 12.6426 | 2.3154 | 10.5514 | 10.5622 | |
|
| 4.0508 | 7.0 | 7000 | 3.3048 | 12.843 | 2.3893 | 10.7232 | 10.7357 | |
|
| 4.0293 | 8.0 | 8000 | 3.2988 | 12.7272 | 2.4338 | 10.5647 | 10.5889 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
