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Meta-Llama-3-8B-VIGGO-qlora
asprenger/Meta-Llama-3-8B-VIGGO-qlora
Meta-Llama-3-8B-VIGGO-qlora is a machine learning model from asprenger. 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 other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- other
- Access
- Public
- Created
- May 10, 2024
- Updated
- May 10, 2024
- SHA
- bb55cd48
Base models
Datasets
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. -->
Meta-Llama-3-8B-VIGGO-qlora
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.6168
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: 8
- 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: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5174 | 0.99 | 25 | 0.5002 |
| 0.4168 | 1.98 | 50 | 0.4846 |
| 0.3898 | 2.97 | 75 | 0.4930 |
| 0.3179 | 4.0 | 101 | 0.5523 |
| 0.2378 | 4.95 | 125 | 0.6168 |
Framework versions
- PEFT 0.10.0
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
- Library
- peft
- License
- other
- Created
- May 10, 2024
- Updated
- May 10, 2024