---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-large-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: germanic_antielite_eng_bert
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# germanic_antielite_eng_bert

This model is a fine-tuned version of [google-bert/bert-large-cased](https://huggingface.co/google-bert/bert-large-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5546
- Accuracy: 0.9183
- F1: 0.5783

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.0773        | 1.0   | 701  | 0.4387          | 0.9194   | 0.5752 |
| 0.057         | 2.0   | 1402 | 0.4246          | 0.9183   | 0.5671 |
| 0.022         | 3.0   | 2103 | 0.5546          | 0.9183   | 0.5783 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3