Downloads · 30 days
5
1% of all-time downloads
distilbert_sst5_padding100model
Realgon/distilbert_sst5_padding100model
distilbert_sst5_padding100model is a text classification model from Realgon. 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
367
Public
Repo size
5.9 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin268 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Nov 28, 2023
- Updated
- Nov 29, 2023
- SHA
- 587a861a
Try a prompt
Base models
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. -->
distilbert_sst5_padding100model
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.6964
- Accuracy: 0.4878
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5744 | 1.0 | 534 | 1.6004 | 0.2308 |
| 1.4231 | 2.0 | 1068 | 1.2088 | 0.4729 |
| 1.1237 | 3.0 | 1602 | 1.1682 | 0.5 |
| 0.9507 | 4.0 | 2136 | 1.2027 | 0.5054 |
| 0.7604 | 5.0 | 2670 | 1.3283 | 0.4995 |
| 0.6266 | 6.0 | 3204 | 1.4933 | 0.4959 |
| 0.488 | 7.0 | 3738 | 1.6948 | 0.4851 |
| 0.3806 | 8.0 | 4272 | 1.8964 | 0.4896 |
| 0.3127 | 9.0 | 4806 | 1.9536 | 0.5014 |
| 0.2609 | 10.0 | 5340 | 2.1723 | 0.4919 |
| 0.2133 | 11.0 | 5874 | 2.4683 | 0.4864 |
| 0.1876 | 12.0 | 6408 | 2.6453 | 0.4941 |
| 0.1634 | 13.0 | 6942 | 2.9011 | 0.4891 |
| 0.1386 | 14.0 | 7476 | 3.0697 | 0.4941 |
| 0.1026 | 15.0 | 8010 | 3.3209 | 0.4900 |
| 0.0909 | 16.0 | 8544 | 3.5261 | 0.4914 |
| 0.0728 | 17.0 | 9078 | 3.5774 | 0.4873 |
| 0.0756 | 18.0 | 9612 | 3.6430 | 0.4891 |
| 0.059 | 19.0 | 10146 | 3.6841 | 0.4873 |
| 0.0476 | 20.0 | 10680 | 3.6964 | 0.4878 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Nov 28, 2023
- Updated
- Nov 29, 2023