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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: BARTModel_ExerciseLog
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. -->
# BARTModel_ExerciseLog
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3574
- Rouge1: 0.8531
- Rouge2: 0.581
- Rougel: 0.8531
- Rougelsum: 0.8531
- Gen Len: 7.2857
## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 18
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 2 | 7.5886 | 0.4437 | 0.1117 | 0.4458 | 0.4459 | 16.5714 |
| No log | 2.0 | 4 | 6.4463 | 0.4127 | 0.1117 | 0.4136 | 0.4155 | 16.0 |
| No log | 3.0 | 6 | 5.9474 | 0.5136 | 0.0952 | 0.5102 | 0.5204 | 8.2857 |
| No log | 4.0 | 8 | 5.6884 | 0.5537 | 0.2381 | 0.5459 | 0.5459 | 8.0 |
| No log | 5.0 | 10 | 5.5303 | 0.55 | 0.2381 | 0.5452 | 0.5452 | 6.5714 |
| No log | 6.0 | 12 | 5.4149 | 0.55 | 0.2381 | 0.5452 | 0.5452 | 6.7143 |
| No log | 7.0 | 14 | 5.2489 | 0.5286 | 0.2 | 0.5197 | 0.5197 | 7.0 |
| No log | 8.0 | 16 | 5.0956 | 0.5388 | 0.2 | 0.5286 | 0.5286 | 7.0 |
| No log | 9.0 | 18 | 4.9528 | 0.5388 | 0.2 | 0.5286 | 0.5286 | 7.0 |
| No log | 10.0 | 20 | 4.8291 | 0.5388 | 0.2 | 0.5286 | 0.5286 | 7.1429 |
| No log | 11.0 | 22 | 4.7158 | 0.5748 | 0.2714 | 0.567 | 0.5667 | 7.4286 |
| No log | 12.0 | 24 | 4.6173 | 0.7388 | 0.3429 | 0.7388 | 0.7388 | 7.2857 |
| No log | 13.0 | 26 | 4.5333 | 0.8531 | 0.581 | 0.8531 | 0.8531 | 7.2857 |
| No log | 14.0 | 28 | 4.4660 | 0.8531 | 0.581 | 0.8531 | 0.8531 | 7.2857 |
| No log | 15.0 | 30 | 4.4177 | 0.8531 | 0.581 | 0.8531 | 0.8531 | 7.2857 |
| No log | 16.0 | 32 | 4.3857 | 0.8531 | 0.581 | 0.8531 | 0.8531 | 7.2857 |
| No log | 17.0 | 34 | 4.3660 | 0.8531 | 0.581 | 0.8531 | 0.8531 | 7.2857 |
| No log | 18.0 | 36 | 4.3574 | 0.8531 | 0.581 | 0.8531 | 0.8531 | 7.2857 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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