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---
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
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