---
license: other
library_name: peft
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
base_model: facebook/opt-350m
model-index:
- name: opt-350m-pattern-based_finetuning_with_lora-mnli-d2_fs1
  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. -->

# opt-350m-pattern-based_finetuning_with_lora-mnli-d2_fs1

This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9441
- Accuracy: 0.5117

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2348        | 1.0   | 1    | 0.9447          | 0.5105   |
| 1.2288        | 2.0   | 2    | 0.9443          | 0.5109   |
| 1.3001        | 3.0   | 3    | 0.9441          | 0.5117   |
| 1.6866        | 4.0   | 4    | 0.9439          | 0.5112   |
| 1.2842        | 5.0   | 5    | 0.9439          | 0.5109   |


### Framework versions

- PEFT 0.7.1.dev0
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0