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---
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LLM_Teach_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_Teach_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: 1.8314
- Rouge1: 0.4848
- Rouge2: 0.215
- Rougel: 0.3765
- Rougelsum: 0.3762
- Gen Len: 44.2945
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.7164 | 1.0 | 625 | 1.7203 | 0.4724 | 0.2088 | 0.3677 | 0.3675 | 44.1491 |
| 1.3424 | 2.0 | 1250 | 1.6998 | 0.4841 | 0.2167 | 0.3705 | 0.3699 | 45.3727 |
| 1.1171 | 3.0 | 1875 | 1.7546 | 0.4824 | 0.2144 | 0.3735 | 0.3735 | 43.7636 |
| 0.8193 | 4.0 | 2500 | 1.8314 | 0.4848 | 0.215 | 0.3765 | 0.3762 | 44.2945 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0
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