Downloads · 30 days
4
13% of all-time downloads
norbert2_sentiment_norec_en_gpu_3000_rader_3
NTCAL/norbert2_sentiment_norec_en_gpu_3000_rader_3
norbert2_sentiment_norec_en_gpu_3000_rader_3 is a text classification model from NTCAL. 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
30
Public
Repo size
8.5 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.4 GB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Mar 14, 2023
- Updated
- Mar 14, 2023
- SHA
- 5c132c11
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. -->
norbert2_sentiment_norec_to_gpu_3000_rader_2
This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6214
- Compute Metrics: :
- Accuracy: 0.69
- Balanced Accuracy: 0.5
- F1 Score: 0.8166
- Recall: 1.0
- Precision: 0.69
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: 128
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Compute Metrics | Accuracy | Balanced Accuracy | F1 Score | Recall | Precision |
|---|---|---|---|---|---|---|---|---|---|
| No log | 0.85 | 5 | 0.6279 | : | 0.6827 | 0.4994 | 0.8102 | 0.9816 | 0.6897 |
| 0.719 | 1.85 | 10 | 0.6217 | : | 0.6897 | 0.4998 | 0.8163 | 0.9995 | 0.6899 |
| 0.719 | 2.85 | 15 | 0.6225 | : | 0.69 | 0.5 | 0.8166 | 1.0 | 0.69 |
| 0.7646 | 3.85 | 20 | 0.6186 | : | 0.69 | 0.5 | 0.8166 | 1.0 | 0.69 |
| 0.7646 | 4.85 | 25 | 0.6214 | : | 0.69 | 0.5 | 0.8166 | 1.0 | 0.69 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 14, 2023
- Updated
- Mar 14, 2023