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---
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
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