t5-base-pt-asqa-cb
This model is a fine-tuned version of din0s/t5-base-msmarco-nlgen-cb on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.7735
- Rougelsum: 26.3056
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rougelsum |
---|---|---|---|---|
No log | 1.0 | 273 | 2.9031 | 24.6325 |
3.2031 | 2.0 | 546 | 2.8656 | 24.9190 |
3.2031 | 3.0 | 819 | 2.8442 | 25.1197 |
3.0839 | 4.0 | 1092 | 2.8303 | 25.2855 |
3.0839 | 5.0 | 1365 | 2.8189 | 25.4891 |
3.0276 | 6.0 | 1638 | 2.8099 | 25.6116 |
3.0276 | 7.0 | 1911 | 2.8036 | 25.7411 |
3.0043 | 8.0 | 2184 | 2.7976 | 25.8238 |
3.0043 | 9.0 | 2457 | 2.7930 | 25.9201 |
2.9791 | 10.0 | 2730 | 2.7890 | 26.0322 |
2.9545 | 11.0 | 3003 | 2.7851 | 26.0934 |
2.9545 | 12.0 | 3276 | 2.7826 | 26.1574 |
2.9344 | 13.0 | 3549 | 2.7802 | 26.2041 |
2.9344 | 14.0 | 3822 | 2.7785 | 26.2330 |
2.9252 | 15.0 | 4095 | 2.7769 | 26.2394 |
2.9252 | 16.0 | 4368 | 2.7756 | 26.2676 |
2.9109 | 17.0 | 4641 | 2.7747 | 26.2864 |
2.9109 | 18.0 | 4914 | 2.7740 | 26.3146 |
2.9103 | 19.0 | 5187 | 2.7736 | 26.2993 |
2.9103 | 20.0 | 5460 | 2.7735 | 26.3056 |
Framework versions
- Transformers 4.23.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1
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