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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
|