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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-swag
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. -->
# bert-base-uncased-swag
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3863
- Accuracy: 0.2929
## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 321
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 63 | 1.4088 | 0.2273 |
| No log | 2.0 | 126 | 1.4448 | 0.2323 |
| No log | 3.0 | 189 | 1.6544 | 0.2323 |
| No log | 4.0 | 252 | 1.8585 | 0.2424 |
| No log | 5.0 | 315 | 1.9976 | 0.2121 |
| No log | 6.0 | 378 | 1.8819 | 0.2071 |
| No log | 7.0 | 441 | 1.3863 | 0.1919 |
| 0.7104 | 8.0 | 504 | 1.3863 | 0.2929 |
| 0.7104 | 9.0 | 567 | 1.3863 | 0.1919 |
| 0.7104 | 10.0 | 630 | 1.3863 | 0.0354 |
| 0.7104 | 11.0 | 693 | 1.3863 | 0.1010 |
| 0.7104 | 12.0 | 756 | 1.3863 | 0.1364 |
| 0.7104 | 13.0 | 819 | 1.3863 | 0.0 |
| 0.7104 | 14.0 | 882 | 1.3863 | 0.1111 |
| 0.7104 | 15.0 | 945 | 1.3863 | 0.0556 |
| 1.4022 | 16.0 | 1008 | 1.3863 | 0.0253 |
| 1.4022 | 17.0 | 1071 | 1.3863 | 0.1970 |
| 1.4022 | 18.0 | 1134 | 1.3863 | 0.0 |
| 1.4022 | 19.0 | 1197 | 1.3863 | 0.0909 |
| 1.4022 | 20.0 | 1260 | 1.3863 | 0.0505 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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