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t5-small-pointer-cstop_artificial
This model is a fine-tuned version of google/mt5-small on the cstop_artificial dataset. It achieves the following results on the evaluation set:
- Loss: 0.0816
- Exact Match: 0.8050
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 |
|---|---|---|---|---|
| 2.08 | 28.5 | 200 | 0.3320 | 0.0376 |
| 0.272 | 57.13 | 400 | 0.1084 | 0.2630 |
| 0.0789 | 85.63 | 600 | 0.0830 | 0.3184 |
| 0.0355 | 114.25 | 800 | 0.0816 | 0.3363 |
| 0.0207 | 142.75 | 1000 | 0.0868 | 0.3292 |
| 0.014 | 171.38 | 1200 | 0.0952 | 0.3399 |
| 0.0099 | 199.88 | 1400 | 0.1089 | 0.3381 |
| 0.0076 | 228.5 | 1600 | 0.1104 | 0.3381 |
| 0.0057 | 257.13 | 1800 | 0.1153 | 0.3292 |
| 0.0048 | 285.63 | 2000 | 0.1153 | 0.3327 |
| 0.004 | 314.25 | 2200 | 0.1206 | 0.3363 |
| 0.0032 | 342.75 | 2400 | 0.1229 | 0.3363 |
| 0.0028 | 371.38 | 2600 | 0.1268 | 0.3381 |
| 0.0023 | 399.88 | 2800 | 0.1288 | 0.3399 |
| 0.002 | 428.5 | 3000 | 0.1292 | 0.3399 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
