Downloads · 30 days
8
9% of all-time downloads
electra-base-discriminator-finetuned-3d-sentiment
venetis/electra-base-discriminator-finetuned-3d-sentiment
electra-base-discriminator-finetuned-3d-sentiment is a text classification model from venetis. 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
92
Public
Repo size
4.8 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin438 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- electra
- Access
- Public
- Created
- Sep 1, 2023
- Updated
- Sep 2, 2023
- SHA
- a28c7718
Try a prompt
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. -->
electra-base-discriminator-finetuned-3d-sentiment
This model is a fine-tuned version of google/electra-base-discriminator on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5887
- Accuracy: 0.7873
- Precision: 0.7897
- Recall: 0.7873
- F1: 0.7864
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 6381
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.797 | 1.0 | 1595 | 0.7075 | 0.7353 | 0.7434 | 0.7353 | 0.7357 |
| 0.5329 | 2.0 | 3190 | 0.6508 | 0.7550 | 0.7646 | 0.7550 | 0.7554 |
| 0.4597 | 3.0 | 4785 | 0.5889 | 0.7702 | 0.7803 | 0.7702 | 0.7695 |
| 0.3918 | 4.0 | 6380 | 0.5887 | 0.7873 | 0.7897 | 0.7873 | 0.7864 |
| 0.3093 | 5.0 | 7975 | 0.6412 | 0.7833 | 0.7877 | 0.7833 | 0.7836 |
| 0.2144 | 6.0 | 9570 | 0.7786 | 0.7844 | 0.7900 | 0.7844 | 0.7851 |
| 0.1507 | 7.0 | 11165 | 0.8455 | 0.7853 | 0.7903 | 0.7853 | 0.7862 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- electra
- License
- apache-2.0
- Created
- Sep 1, 2023
- Updated
- Sep 2, 2023