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library_name: transformers
license: apache-2.0
base_model: studio-ousia/mluke-base
tags:
- generated_from_trainer
metrics:
- accuracy
- rouge
model-index:
- name: 08cac0e7fc2540de88af08514b4cd03e
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. -->
# 08cac0e7fc2540de88af08514b4cd03e
This model is a fine-tuned version of [studio-ousia/mluke-base](https://huggingface.co/studio-ousia/mluke-base) on the fancyzhx/dbpedia_14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0577
- Data Size: 1.0
- Epoch Runtime: 1586.1733
- Accuracy: 0.9893
- F1 Macro: 0.9893
- Rouge1: 0.9893
- Rouge2: 0.0
- Rougel: 0.9893
- Rougelsum: 0.9893
## 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
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:------:|:---------------:|:---------:|:-------------:|:--------:|:--------:|:------:|:------:|:------:|:---------:|
| No log | 0 | 0 | 2.6273 | 0 | 54.8888 | 0.0830 | 0.0440 | 0.0831 | 0.0 | 0.0830 | 0.0831 |
| 0.1405 | 1 | 17500 | 0.0760 | 0.0078 | 67.3486 | 0.9838 | 0.9839 | 0.9838 | 0.0 | 0.9838 | 0.9838 |
| 0.0611 | 2 | 35000 | 0.0727 | 0.0156 | 79.5771 | 0.9857 | 0.9857 | 0.9857 | 0.0 | 0.9857 | 0.9857 |
| 0.0641 | 3 | 52500 | 0.0825 | 0.0312 | 103.3333 | 0.9836 | 0.9835 | 0.9836 | 0.0 | 0.9836 | 0.9836 |
| 0.0614 | 4 | 70000 | 0.0638 | 0.0625 | 150.7420 | 0.9867 | 0.9867 | 0.9867 | 0.0 | 0.9866 | 0.9867 |
| 0.0472 | 5 | 87500 | 0.0638 | 0.125 | 244.0766 | 0.9871 | 0.9870 | 0.9871 | 0.0 | 0.9870 | 0.9871 |
| 0.0591 | 6 | 105000 | 0.0506 | 0.25 | 430.5615 | 0.9887 | 0.9887 | 0.9887 | 0.0 | 0.9887 | 0.9887 |
| 0.0004 | 7 | 122500 | 0.0464 | 0.5 | 817.6506 | 0.9897 | 0.9897 | 0.9898 | 0.0 | 0.9897 | 0.9897 |
| 0.042 | 8.0 | 140000 | 0.0485 | 1.0 | 1586.6349 | 0.9906 | 0.9906 | 0.9907 | 0.0 | 0.9907 | 0.9906 |
| 0.0325 | 9.0 | 157500 | 0.0513 | 1.0 | 1582.4599 | 0.9897 | 0.9897 | 0.9897 | 0.0 | 0.9897 | 0.9897 |
| 0.0216 | 10.0 | 175000 | 0.0649 | 1.0 | 1581.0572 | 0.9890 | 0.9889 | 0.9890 | 0.0 | 0.9889 | 0.9890 |
| 0.0431 | 11.0 | 192500 | 0.0577 | 1.0 | 1586.1733 | 0.9893 | 0.9893 | 0.9893 | 0.0 | 0.9893 | 0.9893 |
### Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1
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