flan-t5-base-finetune
This model is a fine-tuned version of htriedman/flan-t5-base-finetune on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0175
- Rouge2 Precision: 0.8828
- Rouge2 Recall: 0.1209
- Rouge2 Fmeasure: 0.2082
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
---|---|---|---|---|---|---|
0.0258 | 1.0 | 54375 | 0.0238 | 0.8678 | 0.119 | 0.2048 |
0.0236 | 2.0 | 108750 | 0.0199 | 0.877 | 0.1203 | 0.2071 |
0.0166 | 3.0 | 163125 | 0.0185 | 0.88 | 0.1206 | 0.2076 |
0.0134 | 4.0 | 217500 | 0.0177 | 0.8824 | 0.1208 | 0.208 |
0.0146 | 5.0 | 271875 | 0.0175 | 0.8828 | 0.1209 | 0.2082 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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