---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-ia-checkpoint
  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-ia-checkpoint

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7216
- Accuracy: 0.7229
- F1 Macro: 0.6963
- Precision Macro: 0.7200
- Recall Macro: 0.6916
- Auc: 0.7626

## 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   | 0.6736          | 0.7261   | 0.7028   | 0.7210          | 0.6981       | 0.7428 |
| No log        | 2.0   | 158  | 0.8024          | 0.7006   | 0.6975   | 0.6995          | 0.7070       | 0.7566 |
| No log        | 3.0   | 237  | 0.9896          | 0.7389   | 0.7226   | 0.7307          | 0.7189       | 0.7613 |
| No log        | 4.0   | 316  | 1.3463          | 0.7229   | 0.7032   | 0.7145          | 0.6992       | 0.7444 |
| No log        | 5.0   | 395  | 1.4706          | 0.7357   | 0.7246   | 0.7256          | 0.7238       | 0.7536 |
| No log        | 6.0   | 474  | 1.6432          | 0.7420   | 0.7264   | 0.7339          | 0.7228       | 0.7518 |
| 0.176         | 7.0   | 553  | 1.7216          | 0.7229   | 0.6963   | 0.7200          | 0.6916       | 0.7626 |
| 0.176         | 8.0   | 632  | 1.7837          | 0.7357   | 0.7078   | 0.7383          | 0.7023       | 0.7596 |
| 0.176         | 9.0   | 711  | 1.7627          | 0.7325   | 0.7129   | 0.7256          | 0.7085       | 0.7611 |
| 0.176         | 10.0  | 790  | 1.7560          | 0.7357   | 0.7188   | 0.7275          | 0.7149       | 0.7610 |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1