metadata
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: TokenizerTestingMTSUFall2024SoftwareEngineering
results: []
TokenizerTestingMTSUFall2024SoftwareEngineering
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5198
- Rouge1: 0.2778
- Rouge2: 0.2234
- Rougel: 0.2686
- Rougelsum: 0.2686
- Gen Len: 18.9697
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: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|---|
| 1.8333 | 1.0 | 12429 | 1.6354 | 0.2717 | 0.2139 | 0.262 | 0.262 | 18.9751 |
| 1.7368 | 2.0 | 24858 | 1.5610 | 0.2763 | 0.2208 | 0.267 | 0.267 | 18.9735 |
| 1.6978 | 3.0 | 37287 | 1.5291 | 0.2777 | 0.2227 | 0.2683 | 0.2682 | 18.9699 |
| 1.7008 | 4.0 | 49716 | 1.5198 | 0.2778 | 0.2234 | 0.2686 | 0.2686 | 18.9697 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1