---
base_model: google/pegasus-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-xsum-finetuned-cnn_dailymail
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# pegasus-xsum-finetuned-cnn_dailymail

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8958
- Rouge1: 45.7795
- Rouge2: 23.3182
- Rougel: 32.9241
- Rougelsum: 42.3126
- Bleu 1: 35.4715
- Bleu 2: 24.0726
- Bleu 3: 17.9591
- Meteor: 32.8897
- Lungime rezumat: 43.3773
- Lungime original: 48.6937

## 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: 5.6e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleu 1  | Bleu 2  | Bleu 3  | Meteor  | Lungime rezumat | Lungime original |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:---------------:|:----------------:|
| 1.1281        | 1.0   | 14330 | 0.9373          | 44.64   | 22.2111 | 32.0228 | 41.1223   | 34.4946 | 23.079  | 17.0673 | 31.8685 | 43.543          | 48.6937          |
| 0.9091        | 2.0   | 28660 | 0.9095          | 45.0713 | 22.7428 | 32.4247 | 41.554    | 34.9397 | 23.5631 | 17.5094 | 32.1814 | 43.3467         | 48.6937          |
| 0.8455        | 3.0   | 42990 | 0.8982          | 45.5457 | 23.1315 | 32.7153 | 42.0349   | 35.2659 | 23.8773 | 17.8174 | 32.7185 | 43.5743         | 48.6937          |
| 0.8076        | 4.0   | 57320 | 0.8958          | 45.7795 | 23.3182 | 32.9241 | 42.3126   | 35.4715 | 24.0726 | 17.9591 | 32.8897 | 43.3773         | 48.6937          |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1