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---
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: Physical_MainSections_PegasusLargeModel
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. -->
# Physical_MainSections_PegasusLargeModel
This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.4319
- Rouge1: 45.5252
- Rouge2: 14.1464
- Rougel: 31.4229
- Rougelsum: 41.3858
- Bertscore Precision: 79.0611
- Bertscore Recall: 82.0495
- Bertscore F1: 80.5201
- Bleu: 0.0938
- Gen Len: 192.3440
## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bertscore Precision | Bertscore Recall | Bertscore F1 | Bleu | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|:------:|:--------:|
| 6.7243 | 0.0622 | 100 | 6.4316 | 35.9433 | 8.9384 | 23.9375 | 31.9391 | 75.7874 | 79.9159 | 77.7871 | 0.0555 | 192.3440 |
| 6.3971 | 0.1244 | 200 | 6.0845 | 38.3256 | 10.9703 | 27.2908 | 34.7128 | 76.6783 | 80.6127 | 78.5859 | 0.0706 | 192.3440 |
| 6.2761 | 0.1866 | 300 | 5.9553 | 40.7647 | 12.2223 | 28.45 | 36.7148 | 77.1954 | 81.0751 | 79.0774 | 0.0807 | 192.3440 |
| 6.0434 | 0.2489 | 400 | 5.8472 | 42.1277 | 12.5854 | 29.1212 | 37.9861 | 77.5784 | 81.2781 | 79.3756 | 0.0839 | 192.3440 |
| 6.0126 | 0.3111 | 500 | 5.7596 | 42.3736 | 12.8329 | 29.4128 | 38.3711 | 77.6752 | 81.4031 | 79.4859 | 0.0852 | 192.3440 |
| 5.9705 | 0.3733 | 600 | 5.6999 | 42.782 | 13.0394 | 29.6295 | 38.5859 | 77.6255 | 81.462 | 79.4875 | 0.0864 | 192.3440 |
| 5.8576 | 0.4355 | 700 | 5.6527 | 43.1782 | 13.1374 | 29.8607 | 39.0053 | 77.9976 | 81.5732 | 79.7363 | 0.0872 | 192.3440 |
| 5.8948 | 0.4977 | 800 | 5.6187 | 43.6171 | 13.2343 | 30.0467 | 39.4409 | 78.0197 | 81.5872 | 79.7542 | 0.0869 | 192.3440 |
| 5.8581 | 0.5599 | 900 | 5.5710 | 44.6985 | 13.6521 | 30.6142 | 40.4634 | 78.5325 | 81.7996 | 80.1244 | 0.0900 | 192.3440 |
| 5.669 | 0.6222 | 1000 | 5.5349 | 45.0937 | 13.8618 | 30.8512 | 40.8417 | 78.6878 | 81.9065 | 80.2571 | 0.0919 | 192.3440 |
| 5.6482 | 0.6844 | 1100 | 5.5042 | 45.0894 | 13.9336 | 31.0576 | 41.0813 | 78.9344 | 81.9388 | 80.4013 | 0.0927 | 192.3440 |
| 5.8084 | 0.7466 | 1200 | 5.4730 | 44.4944 | 13.6928 | 30.9811 | 40.6992 | 78.8689 | 81.8742 | 80.3361 | 0.0910 | 192.3440 |
| 5.6847 | 0.8088 | 1300 | 5.4582 | 45.1825 | 14.0216 | 31.2665 | 41.128 | 79.0426 | 81.9989 | 80.4862 | 0.0928 | 192.3440 |
| 5.6545 | 0.8710 | 1400 | 5.4444 | 45.5502 | 14.1713 | 31.3938 | 41.3877 | 79.0623 | 82.0733 | 80.5322 | 0.0942 | 192.3440 |
| 5.5869 | 0.9332 | 1500 | 5.4363 | 45.545 | 14.1516 | 31.4241 | 41.4205 | 79.1346 | 82.0625 | 80.5647 | 0.0939 | 192.3440 |
| 5.7046 | 0.9955 | 1600 | 5.4319 | 45.5252 | 14.1464 | 31.4229 | 41.3858 | 79.0611 | 82.0495 | 80.5201 | 0.0938 | 192.3440 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1
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