---
license: other
base_model: varun-v-rao/opt-350m-fp-sick
tags:
- generated_from_trainer
datasets:
- snli
metrics:
- accuracy
model-index:
- name: opt-350m-fp-sick-lora-snli-model1
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: snli
      type: snli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8440357650883966
---

<!-- 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-fp-sick-lora-snli-model1

This model is a fine-tuned version of [varun-v-rao/opt-350m-fp-sick](https://huggingface.co/varun-v-rao/opt-350m-fp-sick) on the snli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4156
- Accuracy: 0.8440

## 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: 128
- eval_batch_size: 64
- seed: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4823        | 1.0   | 4292 | 0.4156          | 0.8440   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0