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---
library_name: transformers
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Abmiguity-factor
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. -->
# Abmiguity-factor
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8537
- Rouge1: 0.5239
- Rouge2: 0.2727
- Rougel: 0.3876
- Rougelsum: 0.3876
- Gen Len: 90.5
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 1 | 1.2998 | 0.3903 | 0.1429 | 0.2699 | 0.2699 | 69.0 |
| No log | 2.0 | 2 | 1.1258 | 0.4737 | 0.202 | 0.3449 | 0.3449 | 77.0 |
| No log | 3.0 | 3 | 1.0220 | 0.4627 | 0.2003 | 0.3372 | 0.3372 | 87.5 |
| No log | 4.0 | 4 | 0.9522 | 0.472 | 0.2042 | 0.3429 | 0.3429 | 85.5 |
| No log | 5.0 | 5 | 0.9162 | 0.4951 | 0.2238 | 0.3814 | 0.3814 | 95.0 |
| No log | 6.0 | 6 | 0.8882 | 0.4951 | 0.2238 | 0.3814 | 0.3814 | 95.0 |
| No log | 7.0 | 7 | 0.8659 | 0.5171 | 0.2652 | 0.4122 | 0.4122 | 97.5 |
| No log | 8.0 | 8 | 0.8537 | 0.5239 | 0.2727 | 0.3876 | 0.3876 | 90.5 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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