---
library_name: transformers
license: apache-2.0
base_model: microsoft/unixcoder-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my-unixcoder-RQ3
  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. -->

# my-unixcoder-RQ3

This model is a fine-tuned version of [microsoft/unixcoder-base](https://huggingface.co/microsoft/unixcoder-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5170
- Accuracy: 0.9459
- F1 Macro: 0.6581
- F1 Weighted: 0.9465

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 0.4074        | 1.0   | 539  | 0.4512          | 0.9250   | 0.2726   | 0.9164      |
| 0.3457        | 2.0   | 1078 | 0.3373          | 0.9445   | 0.5980   | 0.9414      |
| 0.2816        | 3.0   | 1617 | 0.3155          | 0.9452   | 0.6540   | 0.9452      |
| 0.2311        | 4.0   | 2156 | 0.3363          | 0.9459   | 0.6412   | 0.9453      |
| 0.1854        | 5.0   | 2695 | 0.3757          | 0.9445   | 0.6623   | 0.9460      |
| 0.1534        | 6.0   | 3234 | 0.4139          | 0.9464   | 0.6674   | 0.9473      |
| 0.1155        | 7.0   | 3773 | 0.4640          | 0.9457   | 0.6627   | 0.9468      |
| 0.1087        | 8.0   | 4312 | 0.4969          | 0.9448   | 0.6585   | 0.9457      |
| 0.0807        | 9.0   | 4851 | 0.5103          | 0.9457   | 0.6551   | 0.9461      |
| 0.0726        | 10.0  | 5390 | 0.5170          | 0.9459   | 0.6581   | 0.9465      |


### Framework versions

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