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---
license: apache-2.0
base_model: google-bert/bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BERT-base
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
This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6524
- Accuracy: 0.4265
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 22 | 1.8763 | 0.2549 |
| No log | 2.0 | 44 | 1.8652 | 0.25 |
| No log | 3.0 | 66 | 1.7901 | 0.3088 |
| No log | 4.0 | 88 | 1.7617 | 0.3235 |
| No log | 5.0 | 110 | 1.7064 | 0.3676 |
| No log | 6.0 | 132 | 1.6792 | 0.4167 |
| No log | 7.0 | 154 | 1.6574 | 0.4216 |
| No log | 8.0 | 176 | 1.6524 | 0.4265 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cpu
- Datasets 2.21.0
- Tokenizers 0.19.1
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