---
base_model: dura-garage/nepberta2nepberta
tags:
- generated_from_trainer
model-index:
- name: finetuning-b2b
  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. -->

# finetuning-b2b

This model is a fine-tuned version of [dura-garage/nepberta2nepberta](https://huggingface.co/dura-garage/nepberta2nepberta) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.0038        | 0.5   | 1000  | 0.0012          |
| 0.0009        | 1.0   | 2000  | 0.0007          |
| 0.0052        | 1.5   | 3000  | 0.0002          |
| 0.0069        | 2.0   | 4000  | 0.0002          |
| 0.0011        | 2.5   | 5000  | 0.0003          |
| 0.0045        | 3.0   | 6000  | 0.0007          |
| 0.0012        | 3.5   | 7000  | 0.0002          |
| 0.0028        | 4.0   | 8000  | 0.0001          |
| 0.0001        | 4.5   | 9000  | 0.0004          |
| 0.0001        | 5.0   | 10000 | 0.0000          |
| 0.0092        | 5.5   | 11000 | 0.0001          |
| 0.0006        | 6.0   | 12000 | 0.0002          |
| 0.0003        | 6.5   | 13000 | 0.0000          |
| 0.0057        | 7.0   | 14000 | 0.0000          |
| 0.0           | 7.5   | 15000 | 0.0000          |
| 0.0093        | 8.0   | 16000 | 0.0000          |
| 0.03          | 8.5   | 17000 | 0.0002          |
| 0.0144        | 9.0   | 18000 | 0.0004          |
| 0.0018        | 9.5   | 19000 | 0.0000          |
| 0.0024        | 10.0  | 20000 | 0.0000          |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.1