Downloads · 30 days
9
3% of all-time downloads
albert-base-v2-finetuned-emotion
bandi2716/albert-base-v2-finetuned-emotion
albert-base-v2-finetuned-emotion is a text classification model from bandi2716. 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
302
Public
Parameters
11.7M
47.5 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors46.8 MB · 94%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- albert
- Access
- Public
- Created
- May 23, 2024
- Updated
- May 23, 2024
- SHA
- 7371bd2f
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. -->
albert-base-v2-finetuned-emotion
This model is a fine-tuned version of albert/albert-base-v2 on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.2451
- Accuracy: 0.912
- F1: 0.9118
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.9011 | 1.0 | 250 | 0.4077 | 0.877 | 0.8776 |
| 0.2633 | 2.0 | 500 | 0.2451 | 0.912 | 0.9118 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- albert
- License
- apache-2.0
- Created
- May 23, 2024
- Updated
- May 23, 2024