transformers tensorboard safetensors pegasus text2text-generation generated_from_trainer base_model:google/pegasus-large autotrain_compatible endpoints_compatible region:us
---
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
- precision
- recall
- f1
model-index:
- name: LLM_Teached_Pegasus
  results: []
---

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# LLM_Teached_Pegasus

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: 1.6606
- Rouge1: 0.4557
- Rouge2: 0.2019
- Rougel: 0.3603
- Rougelsum: 0.3597
- Gen Len: 30.8509
- Precision: 0.9078
- Recall: 0.9053
- F1: 0.9064

## 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: 8
- 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
| 2.0887        | 1.0   | 625  | 1.7362          | 0.4326 | 0.1871 | 0.3375 | 0.3373    | 31.2482 | 0.9035    | 0.9015 | 0.9023 |
| 1.8362        | 2.0   | 1250 | 1.6844          | 0.4466 | 0.1942 | 0.3511 | 0.3507    | 30.3036 | 0.9071    | 0.9032 | 0.905  |
| 1.7784        | 3.0   | 1875 | 1.6666          | 0.451  | 0.1992 | 0.3554 | 0.3551    | 30.7991 | 0.907     | 0.9045 | 0.9056 |
| 1.7261        | 4.0   | 2500 | 1.6606          | 0.4557 | 0.2019 | 0.3603 | 0.3597    | 30.8509 | 0.9078    | 0.9053 | 0.9064 |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0
