---
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_3
  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_3

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: 1.3146
- Accuracy: 0.6245

## 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: 0.0002
- train_batch_size: 64
- eval_batch_size: 64
- 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   | 39   | 0.6537          | 0.6065   |
| No log        | 2.0   | 78   | 0.6883          | 0.5596   |
| No log        | 3.0   | 117  | 0.8331          | 0.6065   |
| No log        | 4.0   | 156  | 0.6815          | 0.6209   |
| No log        | 5.0   | 195  | 1.1783          | 0.5740   |
| No log        | 6.0   | 234  | 1.0222          | 0.5921   |
| No log        | 7.0   | 273  | 1.0504          | 0.5957   |
| No log        | 8.0   | 312  | 1.0285          | 0.5921   |
| No log        | 9.0   | 351  | 1.1737          | 0.6029   |
| No log        | 10.0  | 390  | 1.3244          | 0.6065   |
| No log        | 11.0  | 429  | 1.0123          | 0.6137   |
| No log        | 12.0  | 468  | 1.3146          | 0.6245   |
| 0.332         | 13.0  | 507  | 1.4058          | 0.6065   |
| 0.332         | 14.0  | 546  | 1.5425          | 0.6245   |
| 0.332         | 15.0  | 585  | 1.4506          | 0.6245   |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1