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---
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LLM_Teached_Bart
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. -->
# LLM_Teached_Bart
This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7715
- Rouge1: 0.4781
- Rouge2: 0.2085
- Rougel: 0.3718
- Rougelsum: 0.372
- Gen Len: 41.3245
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.6623 | 1.0 | 1250 | 1.6705 | 0.4681 | 0.2057 | 0.3632 | 0.3631 | 43.4718 |
| 1.2986 | 2.0 | 2500 | 1.6330 | 0.476 | 0.2105 | 0.3732 | 0.3737 | 39.9745 |
| 1.0401 | 3.0 | 3750 | 1.7081 | 0.4792 | 0.2134 | 0.3762 | 0.3763 | 40.6155 |
| 0.8853 | 4.0 | 5000 | 1.7715 | 0.4781 | 0.2085 | 0.3718 | 0.372 | 41.3245 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0
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