metadata
base_model: google/pegasus-x-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: cdc_influenza_pagasus-x-large
results: []
cdc_influenza_pagasus-x-large
This model is a fine-tuned version of google/pegasus-x-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0621
- Rouge1: 0.6667
- Rouge2: 0.6562
- Rougel: 0.6667
- Rougelsum: 0.6667
- Gen Len: 51.0
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: 32
- eval_batch_size: 32
- seed: 42
- 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 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 1 | 0.3086 | 0.2386 | 0.2184 | 0.2386 | 0.2386 | 176.0 |
| No log | 2.0 | 2 | 0.1118 | 0.6667 | 0.6562 | 0.6667 | 0.6667 | 51.0 |
| No log | 3.0 | 3 | 0.0755 | 0.6667 | 0.6562 | 0.6667 | 0.6667 | 51.0 |
| No log | 4.0 | 4 | 0.0621 | 0.6667 | 0.6562 | 0.6667 | 0.6667 | 51.0 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2