---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
- precision
- recall
- f1
model-index:
- name: BART_CNNDM_ORIGIN
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BART_CNNDM_ORIGIN

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6921
- Rouge1: 0.3423
- Rouge2: 0.144
- Rougel: 0.2434
- Rougelsum: 0.3142
- Gen Len: 73.4636
- Precision: 0.8695
- Recall: 0.8927
- F1: 0.8808

## 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: 4
- 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: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
| 1.2137        | 1.0   | 625  | 1.6451          | 0.3343 | 0.1359 | 0.2346 | 0.3043    | 72.7655 | 0.8678    | 0.891  | 0.8791 |
| 1.054         | 2.0   | 1250 | 1.6921          | 0.3423 | 0.144  | 0.2434 | 0.3142    | 73.4636 | 0.8695    | 0.8927 | 0.8808 |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0