transformers tensorboard safetensors bart text-classification generated_from_trainer dataset:stanfordnlp/snli base_model:facebook/bart-base base_model:finetune:facebook/bart-base license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/bart-base
datasets:
- stanfordnlp/snli
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bart-base-lora-885K-snli-model3
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: snli
      type: stanfordnlp/snli
    metrics:
    - type: accuracy
      value: 0.8247307457833774
      name: Accuracy
---

<!-- 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. -->

# bart-base-lora-885K-snli-model3

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the snli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4536
- Accuracy: 0.8247

## 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: 256
- eval_batch_size: 128
- seed: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6404        | 1.0   | 2146 | 0.5163          | 0.7920   |
| 0.5797        | 2.0   | 4292 | 0.4646          | 0.8205   |
| 0.5613        | 3.0   | 6438 | 0.4536          | 0.8247   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
