metadata
tags:
- generated_from_trainer
model-index:
- name: GraphCodeBert-Moreepcohs
results: []
GraphCodeBert-Moreepcohs
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.3134
- Rouge2 Precision: 0.259
- Rouge2 Recall: 0.2528
- Rouge2 Fmeasure: 0.25
- Bleu Score: 0.2387
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | Bleu Score |
|---|---|---|---|---|---|---|---|
| 5.8439 | 0.87 | 1500 | 4.1071 | 0.1478 | 0.1394 | 0.139 | 0.1384 |
| 3.7868 | 1.73 | 3000 | 3.6540 | 0.1742 | 0.1731 | 0.1697 | 0.1777 |
| 3.4877 | 2.6 | 4500 | 3.4311 | 0.205 | 0.1966 | 0.1959 | 0.193 |
| 3.0162 | 3.46 | 6000 | 3.3283 | 0.2249 | 0.2162 | 0.2142 | 0.2124 |
| 2.9085 | 4.33 | 7500 | 3.2684 | 0.2418 | 0.2312 | 0.2303 | 0.2233 |
| 2.5761 | 5.2 | 9000 | 3.2578 | 0.2427 | 0.2398 | 0.2354 | 0.2293 |
| 2.4163 | 6.06 | 10500 | 3.3048 | 0.2596 | 0.2516 | 0.2498 | 0.2386 |
| 2.2094 | 6.93 | 12000 | 3.2825 | 0.2561 | 0.2529 | 0.2492 | 0.2396 |
| 2.0907 | 7.79 | 13500 | 3.3134 | 0.259 | 0.2528 | 0.25 | 0.2387 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2