Downloads · 30 days
8
15% of all-time downloads
GPT-NepSA-T2
raygx/GPT-NepSA-T2
GPT-NepSA-T2 is a text classification model from raygx. Use it when you need a label for a piece of text. It is set up for transformers.
probably proofread and complete it, then remove this comment. --
All-time downloads
54
Public
Repo size
497 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.h5497 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- gpt2
- Access
- Public
- Created
- Jul 19, 2023
- Updated
- Jul 19, 2023
- SHA
- dd0ae596
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
GPT-NepSA-T2
This model is a fine-tuned version of raygx/Nepali-GPT2-CausalLM on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.4349
- Validation Loss: 0.7017
- Epoch: 4
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 5e-06, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.005}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 0.7875 | 0.6565 | 0 |
| 0.6364 | 0.6237 | 1 |
| 0.5681 | 0.6358 | 2 |
| 0.5018 | 0.6602 | 3 |
| 0.4349 | 0.7017 | 4 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- gpt2
- Created
- Jul 19, 2023
- Updated
- Jul 19, 2023