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GPT2_Pirate
Nielzac/GPT2_Pirate
GPT2_Pirate is a machine learning model from Nielzac. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- mit
- Access
- Public
- Created
- May 10, 2024
- Updated
- May 10, 2024
- SHA
- 8b9df338
Base models
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_Pirate_2024_05_10_20_25_24_lora_weightTrue_loraR32_optim_adamw_torch_epoch2_lr3e-05
This model is a fine-tuned version of openai-community/gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7723
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.3874 | 0.0673 | 1000 | 1.9785 |
| 1.7367 | 0.1346 | 2000 | 1.8709 |
| 1.6208 | 0.2020 | 3000 | 1.8520 |
| 1.5521 | 0.2693 | 4000 | 1.8361 |
| 1.5165 | 0.3366 | 5000 | 1.8298 |
| 1.484 | 0.4039 | 6000 | 1.8227 |
| 1.4262 | 0.4712 | 7000 | 1.8078 |
| 1.4701 | 0.5385 | 8000 | 1.8000 |
| 1.4188 | 0.6059 | 9000 | 1.7938 |
| 1.403 | 0.6732 | 10000 | 1.7908 |
| 1.4115 | 0.7405 | 11000 | 1.7940 |
| 1.4153 | 0.8078 | 12000 | 1.7888 |
| 1.3903 | 0.8751 | 13000 | 1.7844 |
| 1.3918 | 0.9424 | 14000 | 1.7830 |
| 1.4018 | 1.0098 | 15000 | 1.7843 |
| 1.3579 | 1.0771 | 16000 | 1.7777 |
| 1.3803 | 1.1444 | 17000 | 1.7776 |
| 1.3545 | 1.2117 | 18000 | 1.7778 |
| 1.3557 | 1.2790 | 19000 | 1.7742 |
| 1.3739 | 1.3463 | 20000 | 1.7769 |
| 1.3538 | 1.4137 | 21000 | 1.7778 |
| 1.3761 | 1.4810 | 22000 | 1.7763 |
| 1.347 | 1.5483 | 23000 | 1.7735 |
| 1.3579 | 1.6156 | 24000 | 1.7729 |
| 1.3581 | 1.6829 | 25000 | 1.7734 |
| 1.3472 | 1.7503 | 26000 | 1.7726 |
| 1.3377 | 1.8176 | 27000 | 1.7752 |
| 1.3243 | 1.8849 | 28000 | 1.7732 |
| 1.369 | 1.9522 | 29000 | 1.7723 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- License
- mit
- Created
- May 10, 2024
- Updated
- May 10, 2024