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---
library_name: transformers
license: apache-2.0
base_model: studio-ousia/luke-base
tags:
- generated_from_trainer
metrics:
- accuracy
- rouge
model-index:
- name: 0f2142e9bd37e0ab1f2155dead0be1e5
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. -->
# 0f2142e9bd37e0ab1f2155dead0be1e5
This model is a fine-tuned version of [studio-ousia/luke-base](https://huggingface.co/studio-ousia/luke-base) on the nyu-mll/glue [cola] dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5325
- Data Size: 1.0
- Epoch Runtime: 25.4994
- Accuracy: 0.8115
- F1 Macro: 0.7662
- Rouge1: 0.8115
- Rouge2: 0.0
- Rougel: 0.8115
- Rougelsum: 0.8115
## 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 | 0.6979 | 0 | 1.4878 | 0.3125 | 0.2391 | 0.3115 | 0.0 | 0.3115 | 0.3125 |
| No log | 1 | 267 | 0.6298 | 0.0078 | 2.3376 | 0.6885 | 0.4078 | 0.6895 | 0.0 | 0.6885 | 0.6885 |
| No log | 2 | 534 | 0.6256 | 0.0156 | 2.1027 | 0.6885 | 0.4078 | 0.6895 | 0.0 | 0.6885 | 0.6885 |
| No log | 3 | 801 | 0.6220 | 0.0312 | 2.7075 | 0.6885 | 0.4078 | 0.6895 | 0.0 | 0.6885 | 0.6885 |
| No log | 4 | 1068 | 0.6202 | 0.0625 | 3.5640 | 0.6885 | 0.4078 | 0.6895 | 0.0 | 0.6885 | 0.6885 |
| 0.0369 | 5 | 1335 | 0.6259 | 0.125 | 5.1721 | 0.6885 | 0.4078 | 0.6895 | 0.0 | 0.6885 | 0.6885 |
| 0.6135 | 6 | 1602 | 0.6199 | 0.25 | 8.1249 | 0.6885 | 0.4078 | 0.6895 | 0.0 | 0.6885 | 0.6885 |
| 0.5898 | 7 | 1869 | 0.5910 | 0.5 | 14.1801 | 0.7168 | 0.5070 | 0.7178 | 0.0 | 0.7168 | 0.7178 |
| 0.4506 | 8.0 | 2136 | 0.4844 | 1.0 | 26.1606 | 0.7939 | 0.7166 | 0.7939 | 0.0 | 0.7939 | 0.7944 |
| 0.3043 | 9.0 | 2403 | 0.5989 | 1.0 | 25.3615 | 0.7852 | 0.6916 | 0.7852 | 0.0 | 0.7861 | 0.7852 |
| 0.2686 | 10.0 | 2670 | 0.6326 | 1.0 | 25.7104 | 0.8057 | 0.7419 | 0.8057 | 0.0 | 0.8057 | 0.8057 |
| 0.1852 | 11.0 | 2937 | 0.7550 | 1.0 | 25.6559 | 0.7891 | 0.7035 | 0.7891 | 0.0 | 0.7900 | 0.7891 |
| 0.2224 | 12.0 | 3204 | 0.5325 | 1.0 | 25.4994 | 0.8115 | 0.7662 | 0.8115 | 0.0 | 0.8115 | 0.8115 |
### Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1
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