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clearpolicy-llama-3-8binstruct-v4
andre-fichel/clearpolicy-llama-3-8binstruct-v4
clearpolicy-llama-3-8binstruct-v4 is a machine learning model from andre-fichel. 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
- Model type
- llama
- Access
- Public
- Created
- May 16, 2024
- Updated
- May 16, 2024
- SHA
- 6942a458
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. -->
clearpolicy-llama-3-8binstruct-v4
This model is a fine-tuned version of NousResearch/Meta-Llama-3-8B-Instruct on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.7051
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 7 | 1.2237 |
| No log | 2.0 | 14 | 0.8634 |
| No log | 3.0 | 21 | 0.7050 |
| No log | 4.0 | 28 | 0.7051 |
Framework versions
- PEFT 0.11.0
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- Type
- llama
- License
- other
- Created
- May 16, 2024
- Updated
- May 16, 2024