---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: jun
  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. -->

# jun

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3480
- Topology Accuracy: 0.9863
- Service Accuracy: 0.9668
- Combined Accuracy: 0.9766

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- 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: 50
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Topology Accuracy | Service Accuracy | Combined Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:----------------:|:-----------------:|
| 0.5891        | 1.0   | 96   | 0.5813          | 0.9629            | 0.7070           | 0.8350            |
| 0.5125        | 2.0   | 192  | 0.5057          | 0.9688            | 0.8027           | 0.8857            |
| 0.3715        | 3.0   | 288  | 0.3680          | 0.9863            | 0.9590           | 0.9727            |
| 0.3339        | 4.0   | 384  | 0.3538          | 0.9824            | 0.9609           | 0.9717            |
| 0.3204        | 5.0   | 480  | 0.3531          | 0.9863            | 0.9668           | 0.9766            |
| 0.3172        | 6.0   | 576  | 0.3500          | 0.9883            | 0.9648           | 0.9766            |
| 0.3035        | 7.0   | 672  | 0.3474          | 0.9844            | 0.9668           | 0.9756            |
| 0.302         | 8.0   | 768  | 0.3556          | 0.9863            | 0.9629           | 0.9746            |
| 0.3211        | 9.0   | 864  | 0.3522          | 0.9883            | 0.9668           | 0.9775            |
| 0.3023        | 10.0  | 960  | 0.3461          | 0.9902            | 0.9688           | 0.9795            |
| 0.3013        | 11.0  | 1056 | 0.3451          | 0.9883            | 0.9688           | 0.9785            |
| 0.3003        | 12.0  | 1152 | 0.3500          | 0.9902            | 0.9688           | 0.9795            |
| 0.3152        | 13.0  | 1248 | 0.3475          | 0.9883            | 0.9688           | 0.9785            |
| 0.3           | 14.0  | 1344 | 0.3474          | 0.9844            | 0.9688           | 0.9766            |
| 0.3029        | 15.0  | 1440 | 0.3480          | 0.9863            | 0.9668           | 0.9766            |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0