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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: my_awesome_model
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. -->
# my_awesome_model
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: 1.0970
- Accuracy: 0.8681
- F1: 0.8376
## 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 1.0 | 167 | 0.3828 | 0.8501 | 0.8031 |
| No log | 2.0 | 334 | 0.4787 | 0.8456 | 0.8275 |
| 0.2101 | 3.0 | 501 | 0.6186 | 0.8666 | 0.8367 |
| 0.2101 | 4.0 | 668 | 0.7201 | 0.8546 | 0.8265 |
| 0.2101 | 5.0 | 835 | 0.7675 | 0.8651 | 0.8346 |
| 0.0339 | 6.0 | 1002 | 0.8561 | 0.8681 | 0.8434 |
| 0.0339 | 7.0 | 1169 | 0.8898 | 0.8681 | 0.8382 |
| 0.0339 | 8.0 | 1336 | 0.9854 | 0.8711 | 0.8436 |
| 0.0069 | 9.0 | 1503 | 0.9919 | 0.8711 | 0.8407 |
| 0.0069 | 10.0 | 1670 | 1.0695 | 0.8561 | 0.8280 |
| 0.0069 | 11.0 | 1837 | 1.0542 | 0.8666 | 0.8349 |
| 0.0007 | 12.0 | 2004 | 1.0896 | 0.8681 | 0.8370 |
| 0.0007 | 13.0 | 2171 | 1.1001 | 0.8666 | 0.8349 |
| 0.0007 | 14.0 | 2338 | 1.0888 | 0.8606 | 0.8312 |
| 0.0012 | 15.0 | 2505 | 1.0970 | 0.8681 | 0.8376 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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