| | --- |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: checkpoints_2_microsoft_deberta_21_9 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # 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 |
| | |
