---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mitre-bert-base-cased
  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. -->

# mitre-bert-base-cased

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0145
- Accuracy: 0.6994

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2761        | 0.68  | 500  | 0.8453          | 0.6864   |
| 0.7448        | 1.36  | 1000 | 0.7566          | 0.7164   |
| 0.6056        | 2.04  | 1500 | 0.7187          | 0.7318   |
| 0.4763        | 2.72  | 2000 | 0.7134          | 0.7307   |
| 0.4276        | 3.41  | 2500 | 0.7604          | 0.7420   |
| 0.3855        | 4.09  | 3000 | 0.7493          | 0.7362   |
| 0.3303        | 4.77  | 3500 | 0.7727          | 0.7423   |
| 0.313         | 5.45  | 4000 | 0.8053          | 0.7263   |
| 0.2948        | 6.13  | 4500 | 0.8555          | 0.7280   |
| 0.2779        | 6.81  | 5000 | 0.8839          | 0.7127   |
| 0.2526        | 7.49  | 5500 | 0.9097          | 0.7144   |
| 0.2576        | 8.17  | 6000 | 0.9421          | 0.7171   |
| 0.2461        | 8.86  | 6500 | 0.9821          | 0.7018   |
| 0.2357        | 9.54  | 7000 | 1.0145          | 0.6994   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2