---
license: mit
tags:
- generated_from_trainer
base_model: microsoft/deberta-v3-large
model-index:
- name: safetune
  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. -->

# safetune

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1197
- Mse: 1.1197

## 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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 1.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.2203        | 0.05  | 50   | 1.8289          | 1.8289 |
| 1.8997        | 0.1   | 100  | 1.7516          | 1.7516 |
| 1.4082        | 0.15  | 150  | 1.3950          | 1.3950 |
| 1.5899        | 0.2   | 200  | 1.9590          | 1.9590 |
| 1.3633        | 0.25  | 250  | 1.3316          | 1.3316 |
| 1.3758        | 0.29  | 300  | 1.2860          | 1.2860 |
| 1.3339        | 0.34  | 350  | 1.2694          | 1.2694 |
| 1.2831        | 0.39  | 400  | 1.3048          | 1.3048 |
| 1.2928        | 0.44  | 450  | 1.2395          | 1.2395 |
| 1.2506        | 0.49  | 500  | 1.4315          | 1.4315 |
| 1.204         | 0.54  | 550  | 1.1596          | 1.1596 |
| 1.1749        | 0.59  | 600  | 1.1995          | 1.1995 |
| 1.134         | 0.64  | 650  | 1.3782          | 1.3782 |
| 1.3097        | 0.69  | 700  | 1.1867          | 1.1867 |
| 1.29          | 0.74  | 750  | 1.2024          | 1.2024 |
| 1.1575        | 0.78  | 800  | 1.1197          | 1.1197 |
| 1.2148        | 0.83  | 850  | 1.1944          | 1.1944 |
| 1.1597        | 0.88  | 900  | 1.2023          | 1.2023 |
| 1.1422        | 0.93  | 950  | 1.1546          | 1.1546 |
| 1.0734        | 0.98  | 1000 | 1.2593          | 1.2593 |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3