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t5-small-pointer-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: 0.1202
- Exact Match: 0.7445
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 32
- 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 |
|---|---|---|---|---|
| 2.1451 | 6.65 | 200 | 0.5966 | 0.0134 |
| 0.4695 | 13.33 | 400 | 0.2264 | 0.2998 |
| 0.2229 | 19.98 | 600 | 0.1446 | 0.4649 |
| 0.1389 | 26.65 | 800 | 0.1227 | 0.5154 |
| 0.097 | 33.33 | 1000 | 0.1213 | 0.5221 |
| 0.0724 | 39.98 | 1200 | 0.1202 | 0.5365 |
| 0.0562 | 46.65 | 1400 | 0.1207 | 0.5436 |
| 0.0457 | 53.33 | 1600 | 0.1240 | 0.5441 |
| 0.0399 | 59.98 | 1800 | 0.1349 | 0.5441 |
| 0.0317 | 66.65 | 2000 | 0.1369 | 0.5477 |
| 0.0271 | 73.33 | 2200 | 0.1409 | 0.5490 |
| 0.0237 | 79.98 | 2400 | 0.1462 | 0.5539 |
| 0.0207 | 86.65 | 2600 | 0.1470 | 0.5517 |
| 0.0188 | 93.33 | 2800 | 0.1505 | 0.5508 |
| 0.0174 | 99.98 | 3000 | 0.1505 | 0.5512 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
