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---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: MTSUSpring2025SoftwareEngineering
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. -->
# MTSUSpring2025SoftwareEngineering
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4151
- Rouge1: 0.3167
- Rouge2: 0.2556
- Rougel: 0.3052
- Rougelsum: 0.3051
- Gen Len: 19.8434
## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.7529 | 1.0 | 14778 | 1.5535 | 0.3091 | 0.2415 | 0.2959 | 0.2958 | 19.8355 |
| 1.6541 | 2.0 | 29556 | 1.4777 | 0.313 | 0.2491 | 0.3006 | 0.3006 | 19.8419 |
| 1.602 | 3.0 | 44334 | 1.4397 | 0.3155 | 0.2534 | 0.3036 | 0.3036 | 19.8513 |
| 1.6015 | 4.0 | 59112 | 1.4211 | 0.3164 | 0.2552 | 0.3049 | 0.3049 | 19.84 |
| 1.569 | 5.0 | 73890 | 1.4151 | 0.3167 | 0.2556 | 0.3052 | 0.3051 | 19.8434 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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