---
library_name: transformers
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7266

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 0.8268        | 0.08   | 1000  | 0.7354          |
| 0.7977        | 0.16   | 2000  | 0.7251          |
| 0.7739        | 0.24   | 3000  | 0.7259          |
| 0.771         | 0.32   | 4000  | 0.7269          |
| 0.7468        | 0.4    | 5000  | 0.7269          |
| 0.751         | 0.48   | 6000  | 0.7501          |
| 0.7483        | 0.56   | 7000  | 0.7502          |
| 0.7443        | 0.64   | 8000  | 0.7253          |
| 0.7294        | 0.72   | 9000  | 0.7309          |
| 0.7309        | 0.8    | 10000 | 0.7260          |
| 0.7424        | 0.88   | 11000 | 0.7304          |
| 0.7348        | 0.96   | 12000 | 0.7276          |
| 0.7421        | 1.04   | 13000 | 0.7327          |
| 0.7333        | 1.12   | 14000 | 0.7417          |
| 0.7444        | 1.2    | 15000 | 0.7296          |
| 0.7463        | 1.28   | 16000 | 0.7257          |
| 0.7324        | 1.3600 | 17000 | 0.7253          |
| 0.7297        | 1.44   | 18000 | 0.7314          |
| 0.7358        | 1.52   | 19000 | 0.7253          |
| 0.7442        | 1.6    | 20000 | 0.7248          |
| 0.7384        | 1.6800 | 21000 | 0.7388          |
| 0.7345        | 1.76   | 22000 | 0.7259          |
| 0.7218        | 1.8400 | 23000 | 0.7284          |
| 0.7426        | 1.92   | 24000 | 0.7253          |
| 0.7375        | 2.0    | 25000 | 0.7389          |
| 0.7443        | 2.08   | 26000 | 0.7305          |
| 0.7286        | 2.16   | 27000 | 0.7258          |
| 0.7269        | 2.24   | 28000 | 0.7264          |
| 0.7391        | 2.32   | 29000 | 0.7270          |
| 0.7377        | 2.4    | 30000 | 0.7283          |
| 0.7319        | 2.48   | 31000 | 0.7329          |
| 0.7352        | 2.56   | 32000 | 0.7254          |
| 0.7141        | 2.64   | 33000 | 0.7285          |
| 0.7317        | 2.7200 | 34000 | 0.7253          |
| 0.7334        | 2.8    | 35000 | 0.7305          |
| 0.7332        | 2.88   | 36000 | 0.7282          |
| 0.7309        | 2.96   | 37000 | 0.7266          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1