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---
base_model: microsoft/graphcodebert-base
tags:
- generated_from_keras_callback
model-index:
- name: ASTBERT-gb-5k-methods
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# ASTBERT-gb-5k-methods
This model is a fine-tuned version of [microsoft/graphcodebert-base](https://huggingface.co/microsoft/graphcodebert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0907
- Train Accuracy: 0.9805
- Epoch: 9
## 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:
- optimizer: {'name': 'Adam', 'learning_rate': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Train Accuracy | Epoch |
|:----------:|:--------------:|:-----:|
| 1.1843 | 0.8888 | 0 |
| 0.5507 | 0.9295 | 1 |
| 0.4962 | 0.9317 | 2 |
| 0.4450 | 0.9353 | 3 |
| 0.3849 | 0.9391 | 4 |
| 0.3208 | 0.9441 | 5 |
| 0.2545 | 0.9514 | 6 |
| 0.1904 | 0.9610 | 7 |
| 0.1351 | 0.9712 | 8 |
| 0.0907 | 0.9805 | 9 |
### Framework versions
- Transformers 4.31.0
- TensorFlow 2.10.0
- Datasets 2.18.0
- Tokenizers 0.13.3
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