---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-cased
tags:
- text-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: trainer
  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-base-cased-legal-keyword-identifier

This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the TalonMeyer/URAP_interview_task_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0491
- Accuracy: 0.9910

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0675        | 1.0   | 1000 | 0.0594          | 0.9895   |
| 0.0351        | 2.0   | 2000 | 0.0408          | 0.9925   |
| 0.0227        | 3.0   | 3000 | 0.0491          | 0.9910   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1