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t5-small-vanilla-top_v2
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: 0.0358
- Exact Match: 0.4268
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 |
|---|---|---|---|---|
| 1.8739 | 0.82 | 200 | 0.1319 | 0.2831 |
| 0.1338 | 1.65 | 400 | 0.0670 | 0.3859 |
| 0.0879 | 2.47 | 600 | 0.0568 | 0.4023 |
| 0.0689 | 3.29 | 800 | 0.0478 | 0.4083 |
| 0.059 | 4.12 | 1000 | 0.0457 | 0.4157 |
| 0.0514 | 4.94 | 1200 | 0.0419 | 0.4178 |
| 0.046 | 5.76 | 1400 | 0.0398 | 0.4202 |
| 0.0422 | 6.58 | 1600 | 0.0396 | 0.4220 |
| 0.0386 | 7.41 | 1800 | 0.0386 | 0.4221 |
| 0.0366 | 8.23 | 2000 | 0.0384 | 0.4233 |
| 0.0346 | 9.05 | 2200 | 0.0370 | 0.4249 |
| 0.0322 | 9.88 | 2400 | 0.0362 | 0.4253 |
| 0.0306 | 10.7 | 2600 | 0.0371 | 0.4258 |
| 0.0297 | 11.52 | 2800 | 0.0361 | 0.4266 |
| 0.029 | 12.35 | 3000 | 0.0358 | 0.4268 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2
