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shawgpt-ft
Ashish1920/shawgpt-ft
shawgpt-ft is a machine learning model from Ashish1920. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Jun 18, 2024
- Updated
- Jun 18, 2024
- SHA
- 46d80e9b
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. -->
shawgpt-ft
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.3791
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.2488 | 0.96 | 6 | 4.7586 |
| 4.7253 | 1.92 | 12 | 4.3709 |
| 4.4109 | 2.88 | 18 | 4.1224 |
| 3.5231 | 4.0 | 25 | 3.9352 |
| 3.987 | 4.96 | 31 | 3.8033 |
| 3.8247 | 5.92 | 37 | 3.6821 |
| 3.7534 | 6.88 | 43 | 3.5636 |
| 3.067 | 8.0 | 50 | 3.4520 |
| 3.4842 | 8.96 | 56 | 3.3944 |
| 3.0348 | 9.6 | 60 | 3.3791 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Jun 18, 2024
- Updated
- Jun 18, 2024