---
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