---
license: apache-2.0
tags:
- generated_from_trainer
base_model: bert-base-uncased
model-index:
- name: mitre-bert-base-uncased
  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-uncased

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: 1.1257

## 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: 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: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.0301        | 2.72  | 1000  | 1.6360          |
| 1.4454        | 5.45  | 2000  | 1.4483          |
| 1.2259        | 8.17  | 3000  | 1.3658          |
| 1.0811        | 10.9  | 4000  | 1.2872          |
| 0.9744        | 13.62 | 5000  | 1.2763          |
| 0.8601        | 16.35 | 6000  | 1.2343          |
| 0.7918        | 19.07 | 7000  | 1.1792          |
| 0.7375        | 21.8  | 8000  | 1.1792          |
| 0.6806        | 24.52 | 9000  | 1.1332          |
| 0.6274        | 27.25 | 10000 | 1.1129          |
| 0.5803        | 29.97 | 11000 | 1.1239          |
| 0.5403        | 32.7  | 12000 | 1.1224          |
| 0.5028        | 35.42 | 13000 | 1.1344          |
| 0.4661        | 38.15 | 14000 | 1.1215          |
| 0.4463        | 40.87 | 15000 | 1.1453          |
| 0.4102        | 43.6  | 16000 | 1.0828          |
| 0.3866        | 46.32 | 17000 | 1.1044          |
| 0.3749        | 49.05 | 18000 | 1.1199          |
| 0.3554        | 51.77 | 19000 | 1.0722          |
| 0.3288        | 54.5  | 20000 | 1.1167          |
| 0.319         | 57.22 | 21000 | 1.1110          |
| 0.3064        | 59.95 | 22000 | 1.0821          |
| 0.2938        | 62.67 | 23000 | 1.0702          |
| 0.2741        | 65.4  | 24000 | 1.0373          |
| 0.2626        | 68.12 | 25000 | 1.1236          |
| 0.2525        | 70.84 | 26000 | 1.0831          |
| 0.2433        | 73.57 | 27000 | 1.0691          |
| 0.2376        | 76.29 | 28000 | 1.0647          |
| 0.2303        | 79.02 | 29000 | 1.0851          |
| 0.2164        | 81.74 | 30000 | 1.0864          |
| 0.2103        | 84.47 | 31000 | 1.0502          |
| 0.2049        | 87.19 | 32000 | 1.0644          |
| 0.2011        | 89.92 | 33000 | 1.0262          |
| 0.2024        | 92.64 | 34000 | 1.0738          |
| 0.1889        | 95.37 | 35000 | 1.0640          |
| 0.1846        | 98.09 | 36000 | 1.1257          |


### Framework versions

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