---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-rte-run_8_best
  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-finetuned-rte-run_8_best

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: 0.8601
- Accuracy: 0.7256

## 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: 6.387670620549943e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 20   | 0.6376          | 0.6426   |
| No log        | 2.0   | 40   | 0.6699          | 0.6968   |
| No log        | 3.0   | 60   | 0.6570          | 0.7148   |
| No log        | 4.0   | 80   | 0.8601          | 0.7256   |
| No log        | 5.0   | 100  | 0.9858          | 0.7004   |
| No log        | 6.0   | 120  | 1.1769          | 0.6823   |
| No log        | 7.0   | 140  | 1.2463          | 0.6895   |
| No log        | 8.0   | 160  | 1.5285          | 0.7004   |
| No log        | 9.0   | 180  | 1.4726          | 0.7004   |
| No log        | 10.0  | 200  | 1.5863          | 0.6859   |
| No log        | 11.0  | 220  | 1.5913          | 0.6823   |
| No log        | 12.0  | 240  | 1.6612          | 0.6968   |
| No log        | 13.0  | 260  | 1.6851          | 0.7040   |
| No log        | 14.0  | 280  | 1.7215          | 0.7040   |
| No log        | 15.0  | 300  | 1.7309          | 0.7076   |


### Framework versions

- Transformers 4.50.2
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1