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---
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-large-finetuned-cnn_dailymail
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. -->
# pegasus-large-finetuned-cnn_dailymail
This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0469
- Rouge1: 45.2373
- Rouge2: 22.4813
- Rougel: 31.8329
- Rougelsum: 41.6862
- Bleu 1: 34.8304
- Bleu 2: 23.4162
- Bleu 3: 17.4357
- Meteor: 35.0815
- Lungime rezumat: 56.5898
- Lungime original: 48.7656
## 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: 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: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu 1 | Bleu 2 | Bleu 3 | Meteor | Lungime rezumat | Lungime original |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:---------------:|:----------------:|
| 1.2058 | 1.0 | 7165 | 1.0640 | 44.5245 | 22.1439 | 31.4275 | 40.9808 | 33.9802 | 22.8183 | 16.9712 | 34.1035 | 55.245 | 48.7656 |
| 1.0602 | 2.0 | 14330 | 1.0534 | 44.7088 | 22.1286 | 31.3398 | 41.0804 | 34.1571 | 22.9231 | 17.0479 | 35.1782 | 59.6166 | 48.7656 |
| 1.0144 | 3.0 | 21495 | 1.0479 | 45.0257 | 22.3325 | 31.7313 | 41.4189 | 34.6084 | 23.227 | 17.2859 | 34.7757 | 56.1443 | 48.7656 |
| 0.9875 | 4.0 | 28660 | 1.0469 | 45.2373 | 22.4813 | 31.8329 | 41.6862 | 34.8304 | 23.4162 | 17.4357 | 35.0815 | 56.5898 | 48.7656 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1
|