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---
library_name: transformers
license: apache-2.0
base_model: bert-large-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-cased-binary-classification
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-large-cased-binary-classification
This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1857
- Accuracy: 0.7548
- F1 Macro: 0.7312
- Precision Macro: 0.7580
- Recall Macro: 0.7246
- Auc: 0.7883
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:------:|
| No log | 1.0 | 79 | 0.6805 | 0.5987 | 0.3818 | 0.7987 | 0.5039 | 0.6079 |
| No log | 2.0 | 158 | 0.6254 | 0.6497 | 0.6490 | 0.6611 | 0.6655 | 0.7395 |
| No log | 3.0 | 237 | 0.6803 | 0.7166 | 0.6941 | 0.7087 | 0.6900 | 0.7563 |
| No log | 4.0 | 316 | 0.7502 | 0.7166 | 0.7106 | 0.7093 | 0.7153 | 0.7784 |
| No log | 5.0 | 395 | 1.1857 | 0.7548 | 0.7312 | 0.7580 | 0.7246 | 0.7883 |
| No log | 6.0 | 474 | 1.4866 | 0.7548 | 0.7312 | 0.7580 | 0.7246 | 0.7798 |
| 0.3165 | 7.0 | 553 | 1.5617 | 0.7420 | 0.7319 | 0.7322 | 0.7316 | 0.7829 |
| 0.3165 | 8.0 | 632 | 1.6626 | 0.7452 | 0.7311 | 0.7366 | 0.7280 | 0.7762 |
| 0.3165 | 9.0 | 711 | 1.7303 | 0.7611 | 0.7423 | 0.7595 | 0.7363 | 0.7768 |
| 0.3165 | 10.0 | 790 | 1.7471 | 0.7452 | 0.7294 | 0.7376 | 0.7255 | 0.7765 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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