my_model-2
This model is a fine-tuned version of FYP19/t5-small-finetuned-wikisql on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0847
- Rouge2 Precision: 0.8004
- Rouge2 Recall: 0.4506
- Rouge2 Fmeasure: 0.5172
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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
---|---|---|---|---|---|---|
0.0414 | 1.0 | 1832 | 0.0620 | 0.7123 | 0.3937 | 0.4486 |
0.0255 | 2.0 | 3664 | 0.0669 | 0.7301 | 0.4035 | 0.4621 |
0.0217 | 3.0 | 5496 | 0.0697 | 0.7895 | 0.4469 | 0.511 |
0.0161 | 4.0 | 7328 | 0.0712 | 0.7569 | 0.4217 | 0.4827 |
0.0115 | 5.0 | 9160 | 0.0763 | 0.7778 | 0.435 | 0.4992 |
0.009 | 6.0 | 10992 | 0.0785 | 0.7751 | 0.4306 | 0.4945 |
0.0057 | 7.0 | 12824 | 0.0825 | 0.7755 | 0.4326 | 0.4963 |
0.0045 | 8.0 | 14656 | 0.0847 | 0.8004 | 0.4506 | 0.5172 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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