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

# jn

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: 0.3406
- Topology Accuracy: 0.9883
- Service Accuracy: 0.9746
- Combined Accuracy: 0.9814

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:----------------:|:-----------------:|
| 0.6178        | 1.0   | 96   | 0.6028          | 0.9805            | 0.7012           | 0.8408            |
| 0.5546        | 2.0   | 192  | 0.5229          | 0.9766            | 0.7109           | 0.8438            |
| 0.4255        | 3.0   | 288  | 0.4324          | 0.9805            | 0.9023           | 0.9414            |
| 0.3934        | 4.0   | 384  | 0.3546          | 0.9805            | 0.9668           | 0.9736            |
| 0.3195        | 5.0   | 480  | 0.3477          | 0.9844            | 0.9648           | 0.9746            |
| 0.3052        | 6.0   | 576  | 0.3458          | 0.9863            | 0.9746           | 0.9805            |
| 0.3139        | 7.0   | 672  | 0.3529          | 0.9863            | 0.9688           | 0.9775            |
| 0.3049        | 8.0   | 768  | 0.3533          | 0.9844            | 0.9707           | 0.9775            |
| 0.3145        | 9.0   | 864  | 0.3517          | 0.9863            | 0.9648           | 0.9756            |
| 0.3025        | 10.0  | 960  | 0.3462          | 0.9883            | 0.9668           | 0.9775            |
| 0.3031        | 11.0  | 1056 | 0.3420          | 0.9902            | 0.9707           | 0.9805            |
| 0.3008        | 12.0  | 1152 | 0.3417          | 0.9883            | 0.9727           | 0.9805            |
| 0.3184        | 13.0  | 1248 | 0.3418          | 0.9883            | 0.9746           | 0.9814            |
| 0.2996        | 14.0  | 1344 | 0.3404          | 0.9883            | 0.9746           | 0.9814            |
| 0.3023        | 15.0  | 1440 | 0.3406          | 0.9883            | 0.9746           | 0.9814            |


### Framework versions

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