---
license: apache-2.0
base_model: bert-large-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-cased-rocstories
  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-rocstories

This model is a fine-tuned version of [bert-large-cased](https://huggingface.co./bert-large-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2812
- Accuracy: 0.9417

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 150  | 0.2881          | 0.8778   |
| No log        | 2.0   | 300  | 0.2023          | 0.9248   |
| No log        | 3.0   | 450  | 0.2607          | 0.9417   |
| 0.2327        | 4.0   | 600  | 0.2812          | 0.9417   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2