Downloads · 30 days
9
3% of all-time downloads
distilbert-base-uncased-finetuned-emotion
LeoTungAnh/distilbert-base-uncased-finetuned-emotion
distilbert-base-uncased-finetuned-emotion is a text classification model from LeoTungAnh. 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
320
Public
Parameters
67M
1.6 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors268 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Feb 7, 2024
- Updated
- Feb 13, 2024
- SHA
- 4948e43d
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. -->
distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1538
- Accuracy: 0.936
- F1: 0.9361
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: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 63 | 0.8113 | 0.745 | 0.6916 |
| No log | 2.0 | 126 | 0.2909 | 0.911 | 0.9107 |
| No log | 3.0 | 189 | 0.2003 | 0.928 | 0.9277 |
| 0.5629 | 4.0 | 252 | 0.1698 | 0.938 | 0.9376 |
| 0.5629 | 5.0 | 315 | 0.1561 | 0.9365 | 0.9364 |
| 0.5629 | 6.0 | 378 | 0.1531 | 0.933 | 0.9334 |
| 0.5629 | 7.0 | 441 | 0.1584 | 0.9355 | 0.9345 |
| 0.1065 | 8.0 | 504 | 0.1493 | 0.9325 | 0.9321 |
| 0.1065 | 9.0 | 567 | 0.1504 | 0.936 | 0.9364 |
| 0.1065 | 10.0 | 630 | 0.1481 | 0.9395 | 0.9395 |
| 0.1065 | 11.0 | 693 | 0.1501 | 0.935 | 0.9353 |
| 0.0684 | 12.0 | 756 | 0.1504 | 0.936 | 0.9360 |
| 0.0684 | 13.0 | 819 | 0.1526 | 0.935 | 0.9352 |
| 0.0684 | 14.0 | 882 | 0.1526 | 0.9355 | 0.9357 |
| 0.0684 | 15.0 | 945 | 0.1538 | 0.936 | 0.9361 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Feb 7, 2024
- Updated
- Feb 13, 2024