| | --- |
| | license: cc-by-4.0 |
| | base_model: deepset/bert-base-cased-squad2 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: bert-11 |
| | 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. --> |
| |
|
| | # bert-11 |
| |
|
| | This model is a fine-tuned version of [deepset/bert-base-cased-squad2](https://huggingface.co/deepset/bert-base-cased-squad2) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 6.8857 |
| |
|
| | ## 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: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 3 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 10.1921 | 0.09 | 5 | 7.0754 | |
| | | 5.8664 | 0.18 | 10 | 5.7086 | |
| | | 5.1625 | 0.27 | 15 | 5.4529 | |
| | | 4.5385 | 0.36 | 20 | 5.3727 | |
| | | 3.897 | 0.45 | 25 | 5.5354 | |
| | | 3.6878 | 0.55 | 30 | 5.3682 | |
| | | 2.9641 | 0.64 | 35 | 5.1507 | |
| | | 2.7122 | 0.73 | 40 | 5.3411 | |
| | | 2.741 | 0.82 | 45 | 5.5691 | |
| | | 2.4612 | 0.91 | 50 | 5.7809 | |
| | | 2.1667 | 1.0 | 55 | 6.0948 | |
| | | 1.9087 | 1.09 | 60 | 6.2781 | |
| | | 1.6097 | 1.18 | 65 | 6.4563 | |
| | | 1.6726 | 1.27 | 70 | 6.5659 | |
| | | 1.4427 | 1.36 | 75 | 6.5445 | |
| | | 1.359 | 1.45 | 80 | 6.5064 | |
| | | 1.3626 | 1.55 | 85 | 6.6096 | |
| | | 1.0693 | 1.64 | 90 | 6.6934 | |
| | | 1.1223 | 1.73 | 95 | 6.7681 | |
| | | 1.0488 | 1.82 | 100 | 6.7284 | |
| | | 0.8296 | 1.91 | 105 | 6.6706 | |
| | | 0.9246 | 2.0 | 110 | 6.7214 | |
| | | 0.7915 | 2.09 | 115 | 6.7793 | |
| | | 0.5945 | 2.18 | 120 | 6.8051 | |
| | | 0.6342 | 2.27 | 125 | 6.7852 | |
| | | 0.513 | 2.36 | 130 | 6.8174 | |
| | | 0.5309 | 2.45 | 135 | 6.8690 | |
| | | 0.5658 | 2.55 | 140 | 6.8917 | |
| | | 0.5028 | 2.64 | 145 | 6.8958 | |
| | | 0.5523 | 2.73 | 150 | 6.9080 | |
| | | 0.4203 | 2.82 | 155 | 6.9098 | |
| | | 0.4735 | 2.91 | 160 | 6.8899 | |
| | | 0.4147 | 3.0 | 165 | 6.8857 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.34.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.14.1 |
| |
|
