Downloads · 30 days
7
2% of all-time downloads
Regression_Roberta
Svetlana0303/Regression_Roberta
Regression_Roberta is a text classification model from Svetlana0303. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
396
Public
Repo size
1.5 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin499 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Feb 9, 2023
- Updated
- Feb 13, 2023
- SHA
- 930fa82b
Try a prompt
Model card
From the Hugging Face model README
<!-- 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. -->
Regression_roberta
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1625
- Mse: 0.1625
- Mae: 0.3187
- R2: 0.9161
- Accuracy: 0.5714
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 7 | 3.0379 | 3.0379 | 1.3888 | -1.8504 | 0.4286 |
| No log | 2.0 | 14 | 2.4610 | 2.4610 | 1.2703 | -1.3091 | 0.4286 |
| No log | 3.0 | 21 | 1.9135 | 1.9135 | 1.3077 | -0.7954 | 0.0 |
| No log | 4.0 | 28 | 1.7647 | 1.7647 | 1.1897 | -0.6557 | 0.1429 |
| No log | 5.0 | 35 | 2.2432 | 2.2432 | 1.1115 | -1.1047 | 0.5714 |
| No log | 6.0 | 42 | 2.3279 | 2.3279 | 1.1562 | -1.1842 | 0.5714 |
| No log | 7.0 | 49 | 1.9694 | 1.9694 | 1.0216 | -0.8478 | 0.5714 |
| No log | 8.0 | 56 | 1.6951 | 1.6951 | 0.9216 | -0.5905 | 0.5714 |
| No log | 9.0 | 63 | 1.5986 | 1.5986 | 0.8898 | -0.4999 | 0.5714 |
| No log | 10.0 | 70 | 1.2021 | 1.2021 | 0.7820 | -0.1279 | 0.5714 |
| No log | 11.0 | 77 | 1.0724 | 1.0724 | 0.8114 | -0.0062 | 0.5714 |
| No log | 12.0 | 84 | 0.7198 | 0.7198 | 0.6954 | 0.3246 | 0.4286 |
| No log | 13.0 | 91 | 0.4436 | 0.4436 | 0.5758 | 0.5838 | 0.4286 |
| No log | 14.0 | 98 | 0.2337 | 0.2337 | 0.4422 | 0.7807 | 0.5714 |
| No log | 15.0 | 105 | 0.1429 | 0.1429 | 0.3187 | 0.8659 | 0.7143 |
| No log | 16.0 | 112 | 0.1090 | 0.1090 | 0.2643 | 0.8977 | 0.8571 |
| No log | 17.0 | 119 | 0.1228 | 0.1228 | 0.2882 | 0.8848 | 0.8571 |
| No log | 18.0 | 126 | 0.1318 | 0.1318 | 0.2713 | 0.8763 | 0.8571 |
| No log | 19.0 | 133 | 0.1270 | 0.1270 | 0.2451 | 0.8809 | 0.8571 |
| No log | 20.0 | 140 | 0.1181 | 0.1181 | 0.2174 | 0.8892 | 0.8571 |
| No log | 21.0 | 147 | 0.1441 | 0.1441 | 0.2630 | 0.8648 | 0.8571 |
| No log | 22.0 | 154 | 0.1749 | 0.1749 | 0.3027 | 0.8359 | 0.8571 |
| No log | 23.0 | 161 | 0.1465 | 0.1465 | 0.2596 | 0.8626 | 0.8571 |
| No log | 24.0 | 168 | 0.1699 | 0.1699 | 0.2918 | 0.8406 | 0.7143 |
| No log | 25.0 | 175 | 0.1877 | 0.1877 | 0.3154 | 0.8239 | 0.7143 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Feb 9, 2023
- Updated
- Feb 13, 2023