Downloads · 30 days
15
23% of all-time downloads
bert_base_train_book_ent_15p_b_stsb
gokulsrinivasagan/bert_base_train_book_ent_15p_b_stsb
bert_base_train_book_ent_15p_b_stsb is a text classification model from gokulsrinivasagan. 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
66
Public
Parameters
109M
2.6 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors438 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Apr 9, 2025
- Updated
- Apr 9, 2025
- SHA
- b8c47e7c
Try a prompt
Base models
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. -->
bert_base_train_book_ent_15p_b_stsb
This model is a fine-tuned version of gokulsrinivasagan/bert_base_train_book_ent_15p_b on the GLUE STSB dataset. It achieves the following results on the evaluation set:
- Loss: 1.2951
- Pearson: 0.6591
- Spearmanr: 0.6587
- Combined Score: 0.6589
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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|---|---|---|---|---|---|---|
| 2.5295 | 1.0 | 23 | 2.4017 | 0.1700 | 0.1509 | 0.1605 |
| 1.7551 | 2.0 | 46 | 1.7177 | 0.4865 | 0.4800 | 0.4833 |
| 1.1407 | 3.0 | 69 | 1.3205 | 0.6458 | 0.6447 | 0.6452 |
| 0.7008 | 4.0 | 92 | 1.4046 | 0.6229 | 0.6242 | 0.6235 |
| 0.4982 | 5.0 | 115 | 1.3286 | 0.6529 | 0.6541 | 0.6535 |
| 0.4169 | 6.0 | 138 | 1.2951 | 0.6591 | 0.6587 | 0.6589 |
| 0.3238 | 7.0 | 161 | 1.3283 | 0.6654 | 0.6641 | 0.6648 |
| 0.2569 | 8.0 | 184 | 1.5101 | 0.6635 | 0.6666 | 0.6650 |
| 0.2327 | 9.0 | 207 | 1.5240 | 0.6582 | 0.6553 | 0.6568 |
| 0.1806 | 10.0 | 230 | 1.3088 | 0.6750 | 0.6726 | 0.6738 |
| 0.1793 | 11.0 | 253 | 1.4244 | 0.6494 | 0.6437 | 0.6466 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Languages
- en
- Created
- Apr 9, 2025
- Updated
- Apr 9, 2025