File size: 3,260 Bytes
f30aa3b 7b43de7 f30aa3b 7b43de7 f30aa3b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
---
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
|