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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7311
- Accuracy: 0.92
## 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: 3e-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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3141 | 0.32 | 500 | 0.3820 | 0.848 |
| 0.2561 | 0.64 | 1000 | 0.3424 | 0.87 |
| 0.241 | 0.96 | 1500 | 0.3350 | 0.894 |
| 0.162 | 1.28 | 2000 | 0.1804 | 0.94 |
| 0.1572 | 1.6 | 2500 | 0.4039 | 0.872 |
| 0.1545 | 1.92 | 3000 | 0.2409 | 0.94 |
| 0.1081 | 2.24 | 3500 | 0.1651 | 0.956 |
| 0.0847 | 2.56 | 4000 | 0.1951 | 0.952 |
| 0.0892 | 2.88 | 4500 | 0.3046 | 0.93 |
| 0.0633 | 3.2 | 5000 | 0.3609 | 0.928 |
| 0.0411 | 3.52 | 5500 | 0.4858 | 0.92 |
| 0.0524 | 3.84 | 6000 | 0.3904 | 0.924 |
| 0.0425 | 4.16 | 6500 | 0.4007 | 0.924 |
| 0.0333 | 4.48 | 7000 | 0.3683 | 0.936 |
| 0.0263 | 4.8 | 7500 | 0.5354 | 0.918 |
| 0.0306 | 5.12 | 8000 | 0.4006 | 0.936 |
| 0.0149 | 5.44 | 8500 | 0.4029 | 0.944 |
| 0.0183 | 5.76 | 9000 | 0.4856 | 0.922 |
| 0.0212 | 6.08 | 9500 | 0.6343 | 0.908 |
| 0.0121 | 6.4 | 10000 | 0.6131 | 0.914 |
| 0.0056 | 6.72 | 10500 | 0.6626 | 0.906 |
| 0.0128 | 7.04 | 11000 | 0.6940 | 0.914 |
| 0.0079 | 7.36 | 11500 | 0.6776 | 0.918 |
| 0.0104 | 7.68 | 12000 | 0.6081 | 0.918 |
| 0.0109 | 8.0 | 12500 | 0.6669 | 0.918 |
| 0.006 | 8.32 | 13000 | 0.6885 | 0.916 |
| 0.0049 | 8.64 | 13500 | 0.6219 | 0.932 |
| 0.0031 | 8.96 | 14000 | 0.5504 | 0.942 |
| 0.0016 | 9.28 | 14500 | 0.6355 | 0.928 |
| 0.001 | 9.6 | 15000 | 0.6703 | 0.924 |
| 0.0031 | 9.92 | 15500 | 0.7311 | 0.92 |
### Framework versions
- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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