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t5-small-vanilla-mtop
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1581
- Exact Match: 0.6331
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 |
|---|---|---|---|---|
| 1.5981 | 6.65 | 200 | 0.1598 | 0.4940 |
| 0.1335 | 13.33 | 400 | 0.1155 | 0.5884 |
| 0.074 | 19.98 | 600 | 0.1046 | 0.6094 |
| 0.0497 | 26.65 | 800 | 0.1065 | 0.6139 |
| 0.0363 | 33.33 | 1000 | 0.1134 | 0.6255 |
| 0.0278 | 39.98 | 1200 | 0.1177 | 0.6313 |
| 0.022 | 46.65 | 1400 | 0.1264 | 0.6255 |
| 0.0183 | 53.33 | 1600 | 0.1260 | 0.6304 |
| 0.0151 | 59.98 | 1800 | 0.1312 | 0.6300 |
| 0.0124 | 66.65 | 2000 | 0.1421 | 0.6277 |
| 0.0111 | 73.33 | 2200 | 0.1405 | 0.6277 |
| 0.0092 | 79.98 | 2400 | 0.1466 | 0.6331 |
| 0.008 | 86.65 | 2600 | 0.1522 | 0.6340 |
| 0.007 | 93.33 | 2800 | 0.1590 | 0.6295 |
| 0.0064 | 99.98 | 3000 | 0.1581 | 0.6331 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2
