---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: Training
  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. -->

# Training

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: 0.1474
- Precision: 0.9421
- Recall: 0.8978
- F1: 0.9194
- Roc Auc: 0.9859
- Krippendorff Alpha: 0.8754

## 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: 6.7e-06
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Roc Auc | Krippendorff Alpha |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:-------:|:------------------:|
| 0.3425        | 1.0   | 247  | 0.3340          | 0.8489    | 0.7859 | 0.8162 | 0.9439  | 0.7187             |
| 0.2554        | 2.0   | 494  | 0.2263          | 0.8225    | 0.9183 | 0.8678 | 0.9651  | 0.7865             |
| 0.2351        | 3.0   | 741  | 0.1885          | 0.9087    | 0.8789 | 0.8936 | 0.9765  | 0.8352             |
| 0.1724        | 4.0   | 988  | 0.1892          | 0.9124    | 0.8798 | 0.8958 | 0.9773  | 0.8388             |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1