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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: semantic-bert-balanced-dataset
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. -->
# semantic-bert-balanced-dataset
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1862
- Accuracy: 0.5448
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 160 | 0.8837 | 0.5746 |
| No log | 2.0 | 320 | 0.9415 | 0.5490 |
| No log | 3.0 | 480 | 1.0334 | 0.5669 |
| 0.7136 | 4.0 | 640 | 1.1917 | 0.5661 |
| 0.7136 | 5.0 | 800 | 1.3571 | 0.5780 |
| 0.7136 | 6.0 | 960 | 1.6461 | 0.5772 |
| 0.2277 | 7.0 | 1120 | 2.1103 | 0.5533 |
| 0.2277 | 8.0 | 1280 | 2.3829 | 0.5584 |
| 0.2277 | 9.0 | 1440 | 2.4821 | 0.5618 |
| 0.0617 | 10.0 | 1600 | 2.7549 | 0.5371 |
| 0.0617 | 11.0 | 1760 | 2.8267 | 0.5499 |
| 0.0617 | 12.0 | 1920 | 2.9028 | 0.5490 |
| 0.0242 | 13.0 | 2080 | 2.9845 | 0.5465 |
| 0.0242 | 14.0 | 2240 | 3.0126 | 0.5541 |
| 0.0242 | 15.0 | 2400 | 3.0791 | 0.5490 |
| 0.0086 | 16.0 | 2560 | 3.0980 | 0.5499 |
| 0.0086 | 17.0 | 2720 | 3.1564 | 0.5456 |
| 0.0086 | 18.0 | 2880 | 3.1723 | 0.5499 |
| 0.0048 | 19.0 | 3040 | 3.1791 | 0.5473 |
| 0.0048 | 20.0 | 3200 | 3.1862 | 0.5448 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.3.0.dev20231224
- Datasets 2.16.0
- Tokenizers 0.15.0
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