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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: 0.6080
- Accuracy: 0.6875
## 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 | 0.7378 | 0.4844 |
| No log | 2.0 | 4 | 0.7276 | 0.4844 |
| No log | 3.0 | 6 | 0.7104 | 0.4844 |
| No log | 4.0 | 8 | 0.6924 | 0.5469 |
| 0.7068 | 5.0 | 10 | 0.6837 | 0.5625 |
| 0.7068 | 6.0 | 12 | 0.6782 | 0.5938 |
| 0.7068 | 7.0 | 14 | 0.6755 | 0.5781 |
| 0.7068 | 8.0 | 16 | 0.6701 | 0.625 |
| 0.7068 | 9.0 | 18 | 0.6644 | 0.625 |
| 0.5803 | 10.0 | 20 | 0.6574 | 0.6406 |
| 0.5803 | 11.0 | 22 | 0.6505 | 0.625 |
| 0.5803 | 12.0 | 24 | 0.6436 | 0.6875 |
| 0.5803 | 13.0 | 26 | 0.6370 | 0.6562 |
| 0.5803 | 14.0 | 28 | 0.6316 | 0.6719 |
| 0.4412 | 15.0 | 30 | 0.6267 | 0.6875 |
| 0.4412 | 16.0 | 32 | 0.6232 | 0.6719 |
| 0.4412 | 17.0 | 34 | 0.6205 | 0.6875 |
| 0.4412 | 18.0 | 36 | 0.6175 | 0.6875 |
| 0.4412 | 19.0 | 38 | 0.6141 | 0.6875 |
| 0.3438 | 20.0 | 40 | 0.6113 | 0.6875 |
| 0.3438 | 21.0 | 42 | 0.6099 | 0.6875 |
| 0.3438 | 22.0 | 44 | 0.6109 | 0.6875 |
| 0.3438 | 23.0 | 46 | 0.6112 | 0.6875 |
| 0.3438 | 24.0 | 48 | 0.6107 | 0.6875 |
| 0.2832 | 25.0 | 50 | 0.6097 | 0.6875 |
| 0.2832 | 26.0 | 52 | 0.6088 | 0.6875 |
| 0.2832 | 27.0 | 54 | 0.6082 | 0.6875 |
| 0.2832 | 28.0 | 56 | 0.6080 | 0.6875 |
| 0.2832 | 29.0 | 58 | 0.6080 | 0.6875 |
| 0.2532 | 30.0 | 60 | 0.6080 | 0.6875 |
### Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3
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