---
license: mit
tags:
- generated_from_trainer
model-index:
- name: gbert-large-finetuned-cust
  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. -->

# gbert-large-finetuned-cust

This model is a fine-tuned version of [deepset/gbert-large](https://huggingface.co/deepset/gbert-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1846

## 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: 2e-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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8251        | 1.0   | 157  | 0.5204          |
| 0.508         | 2.0   | 314  | 0.3953          |
| 0.4009        | 3.0   | 471  | 0.3242          |
| 0.3587        | 4.0   | 628  | 0.3300          |
| 0.3276        | 5.0   | 785  | 0.3137          |
| 0.302         | 6.0   | 942  | 0.2826          |
| 0.2777        | 7.0   | 1099 | 0.2768          |
| 0.2609        | 8.0   | 1256 | 0.2726          |
| 0.244         | 9.0   | 1413 | 0.2660          |
| 0.2274        | 10.0  | 1570 | 0.2391          |
| 0.2132        | 11.0  | 1727 | 0.2353          |
| 0.2014        | 12.0  | 1884 | 0.2134          |
| 0.1835        | 13.0  | 2041 | 0.2278          |
| 0.1896        | 14.0  | 2198 | 0.2110          |
| 0.1974        | 15.0  | 2355 | 0.2132          |
| 0.1775        | 16.0  | 2512 | 0.1973          |
| 0.1715        | 17.0  | 2669 | 0.1941          |
| 0.1777        | 18.0  | 2826 | 0.2105          |
| 0.1741        | 19.0  | 2983 | 0.2127          |
| 0.1607        | 20.0  | 3140 | 0.1762          |
| 0.1562        | 21.0  | 3297 | 0.2095          |
| 0.1548        | 22.0  | 3454 | 0.1805          |
| 0.1534        | 23.0  | 3611 | 0.1852          |
| 0.1484        | 24.0  | 3768 | 0.1773          |
| 0.1473        | 25.0  | 3925 | 0.1759          |
| 0.1354        | 26.0  | 4082 | 0.1734          |
| 0.136         | 27.0  | 4239 | 0.1902          |
| 0.1306        | 28.0  | 4396 | 0.1769          |
| 0.1353        | 29.0  | 4553 | 0.1705          |
| 0.1368        | 30.0  | 4710 | 0.1846          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3