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: 1.5834
- Rouge1: 0.2719
- Rouge2: 0.2175
- Rougel: 0.2629
- Rougelsum: 0.2629
- Gen Len: 18.9753
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 |
---|---|---|---|---|---|---|---|---|
1.8415 | 1.0 | 12975 | 1.6850 | 0.2704 | 0.2117 | 0.2604 | 0.2604 | 18.9826 |
1.7849 | 2.0 | 25950 | 1.6190 | 0.2713 | 0.2159 | 0.2621 | 0.262 | 18.9747 |
1.7692 | 3.0 | 38925 | 1.5916 | 0.2718 | 0.2172 | 0.2628 | 0.2627 | 18.9762 |
1.74 | 4.0 | 51900 | 1.5834 | 0.2719 | 0.2175 | 0.2629 | 0.2629 | 18.9753 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1