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---
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LifePrincipalPegasusLarge
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. -->
# LifePrincipalPegasusLarge
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: 5.6547
- Rouge1: 43.3679
- Rouge2: 10.9243
- Rougel: 27.4864
- Rougelsum: 40.3896
- Gen Len: 227.7642
## 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 | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 6.8795 | 0.0881 | 100 | 6.5014 | 32.7482 | 6.8933 | 21.4622 | 30.1026 | 227.7642 |
| 6.4726 | 0.1762 | 200 | 6.2112 | 37.0799 | 8.9306 | 24.652 | 34.5305 | 227.7642 |
| 6.2749 | 0.2643 | 300 | 6.0775 | 38.9836 | 9.7478 | 25.6809 | 36.2375 | 227.7642 |
| 6.2445 | 0.3524 | 400 | 5.9878 | 39.9961 | 10.0625 | 25.9686 | 37.4853 | 227.7642 |
| 6.1752 | 0.4405 | 500 | 5.8898 | 40.1077 | 10.1194 | 26.1056 | 37.4283 | 227.7642 |
| 6.0343 | 0.5286 | 600 | 5.8116 | 41.7626 | 10.4065 | 26.7348 | 38.9953 | 227.7642 |
| 6.0009 | 0.6167 | 700 | 5.7529 | 42.0869 | 10.5523 | 26.9037 | 39.3663 | 227.7642 |
| 5.9523 | 0.7048 | 800 | 5.7057 | 42.4863 | 10.6188 | 27.1573 | 39.6282 | 227.7642 |
| 5.9445 | 0.7929 | 900 | 5.6786 | 42.4071 | 10.6897 | 27.1549 | 39.5086 | 227.7642 |
| 5.8047 | 0.8810 | 1000 | 5.6646 | 43.4098 | 10.9746 | 27.4646 | 40.4014 | 227.7642 |
| 5.8718 | 0.9691 | 1100 | 5.6547 | 43.3679 | 10.9243 | 27.4864 | 40.3896 | 227.7642 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1
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