---
library_name: transformers
base_model: microsoft/codebert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: codebert-td
  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. -->

# codebert-td

This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4325
- Accuracy: 0.9492
- F1 Macro: 0.6372
- F1 Weighted: 0.9487

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 0.3710        | 1.0   | 539  | 0.3667          | 0.9399   | 0.2785   | 0.9265      |
| 0.3190        | 2.0   | 1078 | 0.3273          | 0.9450   | 0.3737   | 0.9394      |
| 0.2832        | 3.0   | 1617 | 0.3055          | 0.9513   | 0.5054   | 0.9483      |
| 0.2518        | 4.0   | 2156 | 0.3008          | 0.9529   | 0.6363   | 0.9515      |
| 0.1736        | 5.0   | 2695 | 0.3219          | 0.9520   | 0.6821   | 0.9520      |
| 0.1768        | 6.0   | 3234 | 0.3548          | 0.9520   | 0.6803   | 0.9518      |
| 0.1445        | 7.0   | 3773 | 0.3569          | 0.9524   | 0.6808   | 0.9525      |
| 0.1154        | 8.0   | 4312 | 0.3944          | 0.9517   | 0.6895   | 0.9522      |
| 0.0974        | 9.0   | 4851 | 0.4116          | 0.9524   | 0.6966   | 0.9527      |
| 0.1000        | 10.0  | 5390 | 0.4149          | 0.9531   | 0.6886   | 0.9532      |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2