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t5-base-adv-mtop
This model is a fine-tuned version of google/mt5-base on the mtop dataset. It achieves the following results on the evaluation set:
- Loss: 0.1009
- Exact Match: 0.7937
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3000
Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match |
|---|---|---|---|---|
| 4.2521 | 1.09 | 200 | 0.1367 | 0.5418 |
| 6.2586 | 2.17 | 400 | 0.1020 | 0.6004 |
| 4.0003 | 3.26 | 600 | 0.1009 | 0.6179 |
| 2.7191 | 4.35 | 800 | 0.1066 | 0.6251 |
| 1.5031 | 5.43 | 1000 | 0.1215 | 0.6286 |
| 0.703 | 6.52 | 1200 | 0.1238 | 0.6215 |
| 0.6371 | 7.61 | 1400 | 0.1365 | 0.6286 |
| 0.3712 | 8.69 | 1600 | 0.1450 | 0.6300 |
| 0.5666 | 9.78 | 1800 | 0.1500 | 0.6295 |
| 0.5237 | 10.87 | 2000 | 0.1416 | 0.6251 |
| 0.4562 | 11.96 | 2200 | 0.1464 | 0.6313 |
| 0.3421 | 13.04 | 2400 | 0.1635 | 0.6277 |
| 0.3686 | 14.13 | 2600 | 0.1643 | 0.6322 |
| 0.218 | 15.22 | 2800 | 0.1800 | 0.6277 |
| 0.2371 | 16.3 | 3000 | 0.1742 | 0.6268 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2
