MTSUSpring2025SoftwareEngineering
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: 1.4151
- 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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Base model
google-t5/t5-small