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t5-small-pointer-adv-mtop
This model is a fine-tuned version of google/mt5-small on the mtop dataset. It achieves the following results on the evaluation set:
- Loss: 0.1341
- Exact Match: 0.5817
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 |
|---|---|---|---|---|
| 2.1628 | 1.09 | 200 | 0.7205 | 0.0022 |
| 1.1208 | 2.17 | 400 | 0.6393 | 0.0013 |
| 0.8675 | 3.26 | 600 | 0.5905 | 0.0027 |
| 1.8729 | 4.35 | 800 | 0.5726 | 0.0031 |
| 3.5417 | 5.43 | 1000 | 0.5371 | 0.0067 |
| 0.9087 | 6.52 | 1200 | 0.3512 | 0.1119 |
| 1.2224 | 7.61 | 1400 | 0.2739 | 0.1911 |
| 0.7597 | 8.69 | 1600 | 0.2151 | 0.3016 |
| 0.6981 | 9.78 | 1800 | 0.1736 | 0.3749 |
| 0.4779 | 10.87 | 2000 | 0.1548 | 0.4166 |
| 0.4397 | 11.96 | 2200 | 0.1377 | 0.4510 |
| 0.4101 | 13.04 | 2400 | 0.1480 | 0.4197 |
| 0.3323 | 14.13 | 2600 | 0.1396 | 0.4398 |
| 0.2565 | 15.22 | 2800 | 0.1351 | 0.4523 |
| 0.2108 | 16.3 | 3000 | 0.1341 | 0.4541 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2
