---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
model-index:
- name: art-bert-base-cased
  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. -->

# art-bert-base-cased

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5202

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 6.6432        | 3.23  | 100  | 5.8478          |
| 5.651         | 6.45  | 200  | 5.5368          |
| 5.1511        | 9.68  | 300  | 5.2206          |
| 4.77          | 12.9  | 400  | 4.9162          |
| 4.449         | 16.13 | 500  | 4.8133          |
| 4.18          | 19.35 | 600  | 4.5716          |
| 3.9485        | 22.58 | 700  | 4.3972          |
| 3.6496        | 25.81 | 800  | 4.2725          |
| 3.4384        | 29.03 | 900  | 4.1514          |
| 3.2557        | 32.26 | 1000 | 4.1532          |
| 3.0924        | 35.48 | 1100 | 3.9699          |
| 2.8789        | 38.71 | 1200 | 3.8153          |
| 2.7001        | 41.94 | 1300 | 3.8936          |
| 2.5654        | 45.16 | 1400 | 3.8185          |
| 2.4543        | 48.39 | 1500 | 3.9040          |
| 2.2817        | 51.61 | 1600 | 3.7283          |
| 2.2239        | 54.84 | 1700 | 3.6337          |
| 2.1119        | 58.06 | 1800 | 3.7746          |
| 1.9952        | 61.29 | 1900 | 3.5909          |
| 1.9466        | 64.52 | 2000 | 3.5679          |
| 1.8244        | 67.74 | 2100 | 3.6370          |
| 1.7837        | 70.97 | 2200 | 3.6295          |
| 1.6972        | 74.19 | 2300 | 3.6373          |
| 1.6845        | 77.42 | 2400 | 3.4213          |
| 1.6453        | 80.65 | 2500 | 3.5497          |
| 1.5759        | 83.87 | 2600 | 3.5886          |
| 1.5506        | 87.1  | 2700 | 3.4016          |
| 1.5294        | 90.32 | 2800 | 3.3665          |
| 1.4915        | 93.55 | 2900 | 3.3038          |
| 1.5035        | 96.77 | 3000 | 3.3139          |
| 1.4601        | 100.0 | 3100 | 3.5202          |


### Framework versions

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