metadata
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: arg-quality-regression
results: []
arg-quality-regression
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0342
- Mse: 0.0342
- Mae: 0.1359
- R2: 0.1353
- Accuracy: 0.9808
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: 11
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0277 | 1.0 | 1512 | 0.0398 | 0.0398 | 0.1450 | -0.0046 | 0.9736 |
| 0.0218 | 2.0 | 3024 | 0.0342 | 0.0342 | 0.1359 | 0.1353 | 0.9808 |
| 0.0169 | 3.0 | 4536 | 0.0367 | 0.0367 | 0.1409 | 0.0717 | 0.9783 |
| 0.0114 | 4.0 | 6048 | 0.0400 | 0.0400 | 0.1477 | -0.0108 | 0.9751 |
| 0.0075 | 5.0 | 7560 | 0.0439 | 0.0439 | 0.1564 | -0.1093 | 0.9704 |
| 0.006 | 6.0 | 9072 | 0.0465 | 0.0465 | 0.1626 | -0.1749 | 0.9661 |
| 0.0051 | 7.0 | 10584 | 0.0429 | 0.0429 | 0.1574 | -0.0851 | 0.9729 |
| 0.0037 | 8.0 | 12096 | 0.0440 | 0.0440 | 0.1590 | -0.1123 | 0.9720 |
| 0.0035 | 9.0 | 13608 | 0.0412 | 0.0412 | 0.1534 | -0.0401 | 0.9755 |
| 0.0029 | 10.0 | 15120 | 0.0415 | 0.0415 | 0.1537 | -0.0487 | 0.9743 |
| 0.0028 | 11.0 | 16632 | 0.0438 | 0.0438 | 0.1589 | -0.1080 | 0.9712 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1