tensorboard generated_from_trainer dataset:stanfordnlp/snli base_model:facebook/bart-large base_model:finetune:facebook/bart-large license:apache-2.0 model-index region:us
---
base_model: facebook/bart-large
datasets:
- stanfordnlp/snli
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bart-large-bn-adapter-3.17M-snli-model1
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: snli
      type: stanfordnlp/snli
    metrics:
    - type: accuracy
      value: 0.9191221296484454
      name: Accuracy
---

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# bart-large-bn-adapter-3.17M-snli-model1

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the snli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2388
- Accuracy: 0.9191

## 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: 32
- eval_batch_size: 32
- seed: 36
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3308        | 1.0   | 17168 | 0.2528          | 0.9099   |
| 0.3118        | 2.0   | 34336 | 0.2433          | 0.9163   |
| 0.3133        | 3.0   | 51504 | 0.2388          | 0.9191   |


### Framework versions

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