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checkpoints_2_microsoft_deberta_21_9
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8635
- Map@3: 0.8558
- Accuracy: 0.76
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Map@3 | Accuracy |
|---|---|---|---|---|---|
| 0.6215 | 0.15 | 300 | 0.6511 | 0.8592 | 0.76 |
| 0.5953 | 0.3 | 600 | 0.6929 | 0.8533 | 0.765 |
| 0.5332 | 0.45 | 900 | 0.6665 | 0.8525 | 0.76 |
| 0.587 | 0.6 | 1200 | 0.6638 | 0.855 | 0.775 |
| 0.5626 | 0.75 | 1500 | 0.6476 | 0.8692 | 0.78 |
| 0.6712 | 0.9 | 1800 | 0.6499 | 0.8700 | 0.785 |
| 0.2181 | 1.05 | 2100 | 0.8619 | 0.8417 | 0.75 |
| 0.2024 | 1.2 | 2400 | 0.8607 | 0.8467 | 0.75 |
| 0.2571 | 1.35 | 2700 | 0.8282 | 0.8483 | 0.75 |
| 0.2407 | 1.5 | 3000 | 0.8297 | 0.8558 | 0.765 |
| 0.2282 | 1.65 | 3300 | 0.8635 | 0.8558 | 0.76 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
