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---
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ft-facebook-bart-large-xsum-on-samsum
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. -->
# ft-facebook-bart-large-xsum-on-samsum
This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co./facebook/bart-large-xsum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4691
- Rouge1: 51.1221
- Rouge2: 25.9275
- Rougel: 41.5903
- Rougelsum: 46.7354
- Gen Len: 26.89
## 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
- training_steps: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log | 0.22 | 100 | 1.5053 | 49.3903 | 24.5197 | 40.7578 | 45.2724 | 26.3272 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.1
|