ALL_mt5-base_15_spider
This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.7395
- Rouge2 Precision: 0.397
- Rouge2 Recall: 0.2374
- Rouge2 Fmeasure: 0.2735
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
---|---|---|---|---|---|---|
7.6173 | 1.0 | 875 | 1.8215 | 0.3407 | 0.1794 | 0.2153 |
0.2111 | 2.0 | 1750 | 3.9411 | 0.3658 | 0.2228 | 0.2572 |
0.1338 | 3.0 | 2625 | 4.4136 | 0.3594 | 0.2184 | 0.2522 |
0.105 | 4.0 | 3500 | 4.4853 | 0.3795 | 0.2302 | 0.264 |
0.0923 | 5.0 | 4375 | 4.4951 | 0.3768 | 0.227 | 0.2606 |
0.0771 | 6.0 | 5250 | 4.5377 | 0.3772 | 0.229 | 0.263 |
0.0666 | 7.0 | 6125 | 4.5821 | 0.3995 | 0.2366 | 0.2732 |
0.0581 | 8.0 | 7000 | 4.7276 | 0.4024 | 0.2375 | 0.2749 |
0.0541 | 9.0 | 7875 | 4.6743 | 0.4072 | 0.2412 | 0.2789 |
0.0495 | 10.0 | 8750 | 4.5628 | 0.3983 | 0.2387 | 0.2748 |
0.0455 | 11.0 | 9625 | 4.5861 | 0.3942 | 0.2363 | 0.2722 |
0.0428 | 12.0 | 10500 | 4.7071 | 0.3867 | 0.2364 | 0.2712 |
0.0417 | 13.0 | 11375 | 4.7196 | 0.3971 | 0.2375 | 0.2739 |
0.0396 | 14.0 | 12250 | 4.7196 | 0.3956 | 0.2371 | 0.2727 |
0.0381 | 15.0 | 13125 | 4.7395 | 0.397 | 0.2374 | 0.2735 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for NatthawatTung/ALL_mt5-base_15_spider
Base model
google/mt5-base