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t5-base-pointer-cstop_artificial
This model is a fine-tuned version of google/mt5-base on the cstop_artificial dataset. It achieves the following results on the evaluation set:
- Loss: 0.0776
- Exact Match: 0.7746
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 |
|---|---|---|---|---|
| 1.7482 | 28.5 | 200 | 0.2505 | 0.1020 |
| 0.1366 | 57.13 | 400 | 0.0776 | 0.3238 |
| 0.0275 | 85.63 | 600 | 0.0881 | 0.3381 |
| 0.0114 | 114.25 | 800 | 0.0990 | 0.3399 |
| 0.0064 | 142.75 | 1000 | 0.1120 | 0.3417 |
| 0.0045 | 171.38 | 1200 | 0.1081 | 0.3435 |
| 0.0036 | 199.88 | 1400 | 0.1230 | 0.3435 |
| 0.0025 | 228.5 | 1600 | 0.1211 | 0.3399 |
| 0.002 | 257.13 | 1800 | 0.1367 | 0.3399 |
| 0.0016 | 285.63 | 2000 | 0.1324 | 0.3435 |
| 0.0013 | 314.25 | 2200 | 0.1340 | 0.3470 |
| 0.001 | 342.75 | 2400 | 0.1374 | 0.3435 |
| 0.0009 | 371.38 | 2600 | 0.1384 | 0.3417 |
| 0.0007 | 399.88 | 2800 | 0.1422 | 0.3435 |
| 0.0006 | 428.5 | 3000 | 0.1452 | 0.3417 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
