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---
base_model: google/pegasus-cnn_dailymail
tags:
- generated_from_trainer
metrics:
- rouge
- precision
- recall
- f1
model-index:
- name: LLM_Teached_PEGASUS_CNNDM
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. -->
# LLM_Teached_PEGASUS_CNNDM
This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8217
- Rouge1: 0.4508
- Rouge2: 0.1963
- Rougel: 0.332
- Rougelsum: 0.3319
- Gen Len: 48.3173
- Precision: 0.9046
- Recall: 0.9045
- F1: 0.9044
## 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: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
| 2.1425 | 1.0 | 625 | 1.8475 | 0.4458 | 0.193 | 0.3283 | 0.3284 | 48.1127 | 0.9038 | 0.9037 | 0.9036 |
| 1.9247 | 2.0 | 1250 | 1.8217 | 0.4508 | 0.1963 | 0.332 | 0.3319 | 48.3173 | 0.9046 | 0.9045 | 0.9044 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0
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