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---
license: mit
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: microsoft/deberta-v3-xsmall
model-index:
- name: STS-Lora-Fine-Tuning-Capstone-Deberta-old-model-pipe
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. -->
# STS-Lora-Fine-Tuning-Capstone-Deberta-old-model-pipe
This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7440
- Accuracy: 0.2429
## 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: 3e-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: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 180 | 1.7590 | 0.2429 |
| No log | 2.0 | 360 | 1.7488 | 0.2429 |
| 1.745 | 3.0 | 540 | 1.7451 | 0.2429 |
| 1.745 | 4.0 | 720 | 1.7440 | 0.2429 |
### Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2