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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-sst-2-32-13-30
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-sst-2-32-13-30
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: 0.5860
- Accuracy: 0.7344
## 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: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 2 | 0.7504 | 0.4844 |
| No log | 2.0 | 4 | 0.7296 | 0.4844 |
| No log | 3.0 | 6 | 0.7038 | 0.4688 |
| No log | 4.0 | 8 | 0.6848 | 0.5 |
| 0.6775 | 5.0 | 10 | 0.6753 | 0.5312 |
| 0.6775 | 6.0 | 12 | 0.6666 | 0.5625 |
| 0.6775 | 7.0 | 14 | 0.6533 | 0.5938 |
| 0.6775 | 8.0 | 16 | 0.6361 | 0.6406 |
| 0.6775 | 9.0 | 18 | 0.6181 | 0.6562 |
| 0.4471 | 10.0 | 20 | 0.6136 | 0.6406 |
| 0.4471 | 11.0 | 22 | 0.6116 | 0.6875 |
| 0.4471 | 12.0 | 24 | 0.6051 | 0.7031 |
| 0.4471 | 13.0 | 26 | 0.5977 | 0.7031 |
| 0.4471 | 14.0 | 28 | 0.5903 | 0.7031 |
| 0.2163 | 15.0 | 30 | 0.5855 | 0.7031 |
| 0.2163 | 16.0 | 32 | 0.5839 | 0.7031 |
| 0.2163 | 17.0 | 34 | 0.5831 | 0.7031 |
| 0.2163 | 18.0 | 36 | 0.5821 | 0.7031 |
| 0.2163 | 19.0 | 38 | 0.5822 | 0.7188 |
| 0.1269 | 20.0 | 40 | 0.5819 | 0.7188 |
| 0.1269 | 21.0 | 42 | 0.5826 | 0.7188 |
| 0.1269 | 22.0 | 44 | 0.5844 | 0.7344 |
| 0.1269 | 23.0 | 46 | 0.5848 | 0.7344 |
| 0.1269 | 24.0 | 48 | 0.5841 | 0.75 |
| 0.0961 | 25.0 | 50 | 0.5841 | 0.7344 |
| 0.0961 | 26.0 | 52 | 0.5848 | 0.7344 |
| 0.0961 | 27.0 | 54 | 0.5854 | 0.7344 |
| 0.0961 | 28.0 | 56 | 0.5858 | 0.7344 |
| 0.0961 | 29.0 | 58 | 0.5859 | 0.7344 |
| 0.0833 | 30.0 | 60 | 0.5860 | 0.7344 |
### Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3
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