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---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: bart-base-finetuned-samsum-en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 46.8825
- task:
type: summarization
name: Summarization
dataset:
name: samsum
type: samsum
config: samsum
split: test
metrics:
- name: ROUGE-1
type: rouge
value: 45.0692
verified: true
- name: ROUGE-2
type: rouge
value: 20.9049
verified: true
- name: ROUGE-L
type: rouge
value: 37.3128
verified: true
- name: ROUGE-LSUM
type: rouge
value: 40.662
verified: true
- name: loss
type: loss
value: 5.763935565948486
verified: true
- name: gen_len
type: gen_len
value: 18.4921
verified: true
---
<!-- 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-base-finetuned-samsum-en
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3676
- Rouge1: 46.8825
- Rouge2: 22.0923
- Rougel: 39.7249
- Rougelsum: 42.9187
## 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: 5.6e-05
- train_batch_size: 10
- eval_batch_size: 10
- 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 | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.5172 | 1.0 | 300 | 2.1613 | 47.4152 | 22.8106 | 39.93 | 43.3639 |
| 0.3627 | 2.0 | 600 | 2.2771 | 47.2676 | 22.6325 | 40.1345 | 43.19 |
| 0.2466 | 3.0 | 900 | 2.3676 | 46.8825 | 22.0923 | 39.7249 | 42.9187 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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