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---
license: mit
tags:
- generated_from_trainer
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
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