Downloads · 30 days
13
2% of all-time downloads
all-MiniLM-L6-v2-quora
rohit1998/all-MiniLM-L6-v2-quora
all-MiniLM-L6-v2-quora is a text classification model from rohit1998. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
683
Public
Repo size
3.9 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin90.9 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Oct 6, 2022
- Updated
- Oct 8, 2022
- SHA
- 07c430e5
Try a prompt
Datasets
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. -->
all-MiniLM-L6-v2-quora
This model is a fine-tuned version of sentence-transformers/all-MiniLM-L6-v2 on the quora dataset. It achieves the following results on the evaluation set:
- Loss: 0.0865
- Accuracy: 0.8150
- F1: 0.7945
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.087 | 1.0 | 11371 | 0.0829 | 0.4143 | 0.5535 |
| 0.0794 | 2.0 | 22742 | 0.0783 | 0.6017 | 0.6458 |
| 0.0606 | 3.0 | 34113 | 0.0756 | 0.3631 | 0.5327 |
| 0.05 | 4.0 | 45484 | 0.0781 | 0.4475 | 0.5679 |
| 0.0448 | 5.0 | 56855 | 0.0789 | 0.6856 | 0.6975 |
| 0.0372 | 6.0 | 68226 | 0.0761 | 0.3922 | 0.5443 |
| 0.033 | 7.0 | 79597 | 0.0786 | 0.7586 | 0.7494 |
| 0.032 | 8.0 | 90968 | 0.0780 | 0.5011 | 0.5927 |
| 0.0229 | 9.0 | 102339 | 0.0819 | 0.7513 | 0.7439 |
| 0.0198 | 10.0 | 113710 | 0.0840 | 0.5522 | 0.6185 |
| 0.0169 | 11.0 | 125081 | 0.0821 | 0.7959 | 0.7785 |
| 0.0199 | 12.0 | 136452 | 0.0807 | 0.8353 | 0.8118 |
| 0.0118 | 13.0 | 147823 | 0.0819 | 0.8418 | 0.8176 |
| 0.0123 | 14.0 | 159194 | 0.0816 | 0.7577 | 0.7487 |
| 0.0093 | 15.0 | 170565 | 0.0856 | 0.7934 | 0.7765 |
| 0.0124 | 16.0 | 181936 | 0.0843 | 0.8484 | 0.8241 |
| 0.008 | 17.0 | 193307 | 0.0838 | 0.7998 | 0.7818 |
| 0.0106 | 18.0 | 204678 | 0.0872 | 0.8245 | 0.8027 |
| 0.0066 | 19.0 | 216049 | 0.0857 | 0.8122 | 0.7922 |
| 0.0059 | 20.0 | 227420 | 0.0865 | 0.8150 | 0.7945 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cu116
- Datasets 2.5.1
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Oct 6, 2022
- Updated
- Oct 8, 2022