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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
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