Downloads · 30 days
8
3% of all-time downloads
tulio-gpt-neo
jorgeortizfuentes/tulio-gpt-neo
tulio-gpt-neo is a text generation model from jorgeortizfuentes. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
296
Public
Repo size
381 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin5.4 GB · 100%
At a glance
- Task
- Text Generation
- Library
- transformers
- License
- mit
- Model type
- gpt_neo
- Access
- Public
- Created
- Feb 15, 2023
- Updated
- Feb 19, 2023
- SHA
- 7ed1d767
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. -->
tulio-gpt-neo
This model is a fine-tuned version of EleutherAI/gpt-neo-2.7B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6494
- Accuracy: 0.6498
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 13
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0707 | 0.06 | 2000 | 1.8760 | 0.6169 |
| 2.0158 | 0.12 | 4000 | 1.8242 | 0.6244 |
| 1.9811 | 0.17 | 6000 | 1.7930 | 0.6289 |
| 1.9313 | 0.23 | 8000 | 1.7695 | 0.6320 |
| 1.9437 | 0.29 | 10000 | 1.7510 | 0.6349 |
| 1.9157 | 0.35 | 12000 | 1.7363 | 0.6371 |
| 1.9071 | 0.41 | 14000 | 1.7227 | 0.6388 |
| 1.871 | 0.47 | 16000 | 1.7100 | 0.6409 |
| 1.8679 | 0.52 | 18000 | 1.7012 | 0.6419 |
| 1.848 | 0.58 | 20000 | 1.6904 | 0.6440 |
| 1.8353 | 0.64 | 22000 | 1.6836 | 0.6449 |
| 1.8603 | 0.7 | 24000 | 1.6768 | 0.6460 |
| 1.844 | 0.76 | 26000 | 1.6699 | 0.6468 |
| 1.8396 | 0.81 | 28000 | 1.6699 | 0.6464 |
| 1.8095 | 0.87 | 30000 | 1.6592 | 0.6483 |
| 1.8149 | 0.93 | 32000 | 1.6553 | 0.6488 |
| 1.8098 | 0.99 | 34000 | 1.6494 | 0.6498 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Text Generation
- Library
- transformers
- Type
- gpt_neo
- License
- mit
- Created
- Feb 15, 2023
- Updated
- Feb 19, 2023