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

# j

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: 0.3746
- Topology Accuracy: 0.9851
- Service Accuracy: 0.9435
- Combined Accuracy: 0.9643

## 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: 5e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:----------------:|:-----------------:|
| 1.016         | 1.0   | 64   | 0.9725          | 0.7411            | 0.6220           | 0.6815            |
| 0.7234        | 2.0   | 128  | 0.6385          | 0.9643            | 0.6935           | 0.8289            |
| 0.6038        | 3.0   | 192  | 0.5826          | 0.9345            | 0.7440           | 0.8393            |
| 0.5014        | 4.0   | 256  | 0.5192          | 0.9583            | 0.7738           | 0.8661            |
| 0.3959        | 5.0   | 320  | 0.4845          | 0.9732            | 0.7768           | 0.875             |
| 0.4165        | 6.0   | 384  | 0.4579          | 0.9762            | 0.8601           | 0.9182            |
| 0.3699        | 7.0   | 448  | 0.4156          | 0.9851            | 0.9286           | 0.9568            |
| 0.3272        | 8.0   | 512  | 0.3777          | 0.9851            | 0.9524           | 0.9688            |
| 0.3091        | 9.0   | 576  | 0.3714          | 0.9851            | 0.9464           | 0.9658            |
| 0.3092        | 10.0  | 640  | 0.3814          | 0.9821            | 0.9464           | 0.9643            |
| 0.3221        | 11.0  | 704  | 0.3811          | 0.9821            | 0.9405           | 0.9613            |
| 0.3033        | 12.0  | 768  | 0.3724          | 0.9851            | 0.9405           | 0.9628            |
| 0.304         | 13.0  | 832  | 0.3741          | 0.9881            | 0.9435           | 0.9658            |
| 0.3051        | 14.0  | 896  | 0.3743          | 0.9851            | 0.9435           | 0.9643            |
| 0.3039        | 15.0  | 960  | 0.3746          | 0.9851            | 0.9435           | 0.9643            |


### Framework versions

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