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gpt2-kl_1_07-hs_cn_decay
Bainbridge/gpt2-kl_1_07-hs_cn_decay
gpt2-kl_1_07-hs_cn_decay is a text generation model from Bainbridge. 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. --
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At a glance
- Task
- Text Generation
- Library
- transformers
- License
- mit
- Model type
- gpt2
- Access
- Public
- Created
- Apr 12, 2023
- Updated
- Apr 16, 2023
- SHA
- fe99a449
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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. -->
gpt2-kl_1_07-hs_cn_decay
This model is a fine-tuned version of gpt2-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5387
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: 8
- eval_batch_size: 4
- seed: 21
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 74.3927 | 0.02 | 10 | 69.5741 |
| 46.8756 | 0.04 | 20 | 32.9634 |
| 14.3637 | 0.06 | 30 | 10.6462 |
| 7.5685 | 0.08 | 40 | 4.2441 |
| 4.4164 | 0.1 | 50 | 2.0652 |
| 2.2355 | 0.12 | 60 | 1.1276 |
| 1.7411 | 0.14 | 70 | 0.8881 |
| 1.5599 | 0.16 | 80 | 0.7747 |
| 1.5609 | 0.18 | 90 | 0.6453 |
| 1.4701 | 0.2 | 100 | 0.6145 |
| 1.3214 | 0.22 | 110 | 0.6367 |
| 1.3795 | 0.24 | 120 | 0.6098 |
| 1.3714 | 0.26 | 130 | 0.5903 |
| 1.5096 | 0.28 | 140 | 0.5764 |
| 1.4983 | 0.3 | 150 | 0.5695 |
| 1.3707 | 0.32 | 160 | 0.5712 |
| 1.2352 | 0.34 | 170 | 0.5689 |
| 1.4272 | 0.36 | 180 | 0.5650 |
| 1.4578 | 0.38 | 190 | 0.5599 |
| 1.2548 | 0.4 | 200 | 0.5577 |
| 1.488 | 0.42 | 210 | 0.5575 |
| 1.3988 | 0.44 | 220 | 0.5518 |
| 1.1963 | 0.46 | 230 | 0.5536 |
| 1.2992 | 0.48 | 240 | 0.5519 |
| 1.1852 | 0.5 | 250 | 0.5517 |
| 1.2691 | 0.52 | 260 | 0.5473 |
| 1.2183 | 0.54 | 270 | 0.5433 |
| 1.3085 | 0.56 | 280 | 0.5443 |
| 1.1756 | 0.58 | 290 | 0.5422 |
| 1.1152 | 0.6 | 300 | 0.5420 |
| 1.2707 | 0.62 | 310 | 0.5391 |
| 1.3634 | 0.64 | 320 | 0.5376 |
| 1.1368 | 0.66 | 330 | 0.5378 |
| 1.1393 | 0.68 | 340 | 0.5378 |
| 1.1335 | 0.7 | 350 | 0.5387 |
Framework versions
- Transformers 4.28.0
- Pytorch 1.11.0+cu113
- Datasets 2.11.0
- Tokenizers 0.12.1
- Task
- Text Generation
- Library
- transformers
- Type
- gpt2
- License
- mit
- Created
- Apr 12, 2023
- Updated
- Apr 16, 2023