---
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
datasets:
- eur-lex-sum
model-index:
- name: BART_no_extraction_V2
  results: []
---

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# BART_no_extraction_V2

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the eur-lex-sum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0427

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.4492        | 1.0   | 69   | 2.2924          |
| 2.2834        | 2.0   | 138  | 2.1161          |
| 2.0586        | 3.0   | 207  | 2.0469          |
| 1.9241        | 4.0   | 276  | 2.0229          |
| 1.8083        | 5.0   | 345  | 2.0068          |
| 1.7006        | 6.0   | 414  | 1.9867          |
| 1.6168        | 7.0   | 483  | 1.9871          |
| 1.5344        | 8.0   | 552  | 2.0058          |
| 1.4678        | 9.0   | 621  | 2.0054          |
| 1.3988        | 10.0  | 690  | 2.0284          |
| 1.3369        | 11.0  | 759  | 2.0427          |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.19.1