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---
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
|