|
--- |
|
license: mit |
|
base_model: hung200504/bert-squadv2 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- covid_qa_deepset |
|
model-index: |
|
- name: bert-squad-covidqa |
|
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-squad-covidqa |
|
|
|
This model is a fine-tuned version of [hung200504/bert-squadv2](https://huggingface.co/hung200504/bert-squadv2) on the covid_qa_deepset dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5141 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 4.1636 | 0.09 | 5 | 1.4553 | |
|
| 0.8433 | 0.18 | 10 | 0.6359 | |
|
| 0.8245 | 0.26 | 15 | 0.5610 | |
|
| 0.5916 | 0.35 | 20 | 0.5416 | |
|
| 0.5899 | 0.44 | 25 | 0.5148 | |
|
| 0.4838 | 0.53 | 30 | 0.4996 | |
|
| 0.4501 | 0.61 | 35 | 0.4929 | |
|
| 0.7377 | 0.7 | 40 | 0.4610 | |
|
| 0.455 | 0.79 | 45 | 0.4645 | |
|
| 0.478 | 0.88 | 50 | 0.4745 | |
|
| 0.3672 | 0.96 | 55 | 0.4803 | |
|
| 0.6509 | 1.05 | 60 | 0.4875 | |
|
| 0.3094 | 1.14 | 65 | 0.5089 | |
|
| 0.3203 | 1.23 | 70 | 0.5751 | |
|
| 0.3955 | 1.32 | 75 | 0.5416 | |
|
| 0.6197 | 1.4 | 80 | 0.4848 | |
|
| 0.455 | 1.49 | 85 | 0.4716 | |
|
| 0.4086 | 1.58 | 90 | 0.4738 | |
|
| 0.5028 | 1.67 | 95 | 0.4818 | |
|
| 0.4953 | 1.75 | 100 | 0.4867 | |
|
| 0.557 | 1.84 | 105 | 0.4826 | |
|
| 0.3139 | 1.93 | 110 | 0.4832 | |
|
| 0.3217 | 2.02 | 115 | 0.4921 | |
|
| 0.4175 | 2.11 | 120 | 0.5056 | |
|
| 0.3471 | 2.19 | 125 | 0.5204 | |
|
| 0.209 | 2.28 | 130 | 0.5321 | |
|
| 0.5151 | 2.37 | 135 | 0.5285 | |
|
| 0.441 | 2.46 | 140 | 0.5141 | |
|
| 0.3022 | 2.54 | 145 | 0.5031 | |
|
| 0.3789 | 2.63 | 150 | 0.5002 | |
|
| 0.2917 | 2.72 | 155 | 0.5041 | |
|
| 0.372 | 2.81 | 160 | 0.5097 | |
|
| 0.4001 | 2.89 | 165 | 0.5105 | |
|
| 0.1803 | 2.98 | 170 | 0.5141 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.1 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|