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t5-large-multiwoz
This model is a fine-tuned version of t5-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0064
- Acc: 1.0
- True Num: 56671
- Num: 56776
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: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
Training results
Training Loss | Epoch | Step | Validation Loss | Acc | True Num | Num |
---|---|---|---|---|---|---|
0.1261 | 1.13 | 1000 | 0.0933 | 0.98 | 55574 | 56776 |
0.0951 | 2.25 | 2000 | 0.0655 | 0.98 | 55867 | 56776 |
0.0774 | 3.38 | 3000 | 0.0480 | 0.99 | 56047 | 56776 |
0.0584 | 4.51 | 4000 | 0.0334 | 0.99 | 56252 | 56776 |
0.042 | 5.64 | 5000 | 0.0222 | 0.99 | 56411 | 56776 |
0.0329 | 6.76 | 6000 | 0.0139 | 1.0 | 56502 | 56776 |
0.0254 | 7.89 | 7000 | 0.0094 | 1.0 | 56626 | 56776 |
0.0214 | 9.02 | 8000 | 0.0070 | 1.0 | 56659 | 56776 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu102
- Datasets 1.15.1
- Tokenizers 0.10.3