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library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: EXP_1_BINARY-bert-base-cased
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. -->
# EXP_1_BINARY-bert-base-cased
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2053
- Precision: 0.8930
- Recall: 0.9180
- F1: 0.9053
- Accuracy: 0.9203
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2233 | 1.0 | 220 | 0.2117 | 0.8846 | 0.9217 | 0.9028 | 0.9176 |
| 0.2101 | 2.0 | 440 | 0.2088 | 0.8824 | 0.9302 | 0.9057 | 0.9196 |
| 0.2012 | 3.0 | 660 | 0.2053 | 0.8930 | 0.9180 | 0.9053 | 0.9203 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.9.1+cu130
- Datasets 4.4.1
- Tokenizers 0.22.1
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