---
license: apache-2.0
tags:
- generated_from_trainer
base_model: bert-large-cased
model-index:
- name: art-des-bert-large-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-des-bert-large-cased

This model is a fine-tuned version of [bert-large-cased](https://huggingface.co./bert-large-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2776

## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8053        | 5.19  | 100  | 1.4663          |
| 1.3212        | 10.39 | 200  | 1.3795          |
| 1.0223        | 15.58 | 300  | 1.3545          |
| 0.8991        | 20.78 | 400  | 1.3239          |
| 0.7579        | 25.97 | 500  | 1.3276          |
| 0.6554        | 31.17 | 600  | 1.3435          |
| 0.5786        | 36.36 | 700  | 1.2276          |
| 0.5386        | 41.56 | 800  | 1.1930          |
| 0.479         | 46.75 | 900  | 1.2091          |
| 0.4336        | 51.95 | 1000 | 1.0554          |
| 0.3776        | 57.14 | 1100 | 1.4044          |
| 0.3582        | 62.34 | 1200 | 1.1651          |
| 0.3343        | 67.53 | 1300 | 1.2394          |
| 0.3093        | 72.73 | 1400 | 1.1313          |
| 0.2952        | 77.92 | 1500 | 1.2107          |
| 0.2845        | 83.12 | 1600 | 1.2804          |
| 0.2585        | 88.31 | 1700 | 1.1700          |
| 0.2548        | 93.51 | 1800 | 1.2391          |
| 0.2581        | 98.7  | 1900 | 1.2776          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2