---
license: mit
base_model: facebook/bart-large-mnli
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bart-large-mnli_17082023T115544
  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. -->

# bart-large-mnli_17082023T115544

This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4791
- Accuracy: 0.9394
- F1: 0.9528

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 142  | 0.2605          | 0.9095   | 0.9307 |
| No log        | 2.0   | 284  | 0.2664          | 0.9183   | 0.9389 |
| No log        | 2.99  | 426  | 0.2562          | 0.9315   | 0.9467 |
| 0.193         | 4.0   | 569  | 0.3992          | 0.9315   | 0.9458 |
| 0.193         | 5.0   | 711  | 0.4185          | 0.9315   | 0.9441 |
| 0.193         | 6.0   | 853  | 0.4918          | 0.9306   | 0.9462 |
| 0.193         | 6.99  | 995  | 0.4584          | 0.9385   | 0.9526 |
| 0.0101        | 8.0   | 1138 | 0.4611          | 0.9367   | 0.9503 |
| 0.0101        | 9.0   | 1280 | 0.4739          | 0.9385   | 0.9518 |
| 0.0101        | 9.98  | 1420 | 0.4791          | 0.9394   | 0.9528 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3