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nt_rvalue-M7B-rv1024-q4bit-template-template
Zaleks/nt_rvalue-M7B-rv1024-q4bit-template-template
nt_rvalue-M7B-rv1024-q4bit-template-template is a machine learning model from Zaleks. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
- Optimizer: awbn8 - Computational datatype: fp16 - Learning rate: 0.00005 - LoRA rank: 1024 - LoRA alpha multiplier: 2 - LoRA dropout: 0.05 - Batch size: 2 - Gradient accumulation: 8 - Gradient checkpointing: Enabled…
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Updated Aug 6, 2024
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At a glance
- Access
- Public
- Created
- Aug 6, 2024
- Updated
- Aug 6, 2024
- SHA
- 368b3e3f
Model card
From the Hugging Face model README
LoRA adapter for Mistral Instruct 7B v0.2
Training details
- Optimizer: awbn8
- Computational datatype: fp16
- Learning rate: 0.00005
- LoRA rank: 1024
- LoRA alpha multiplier: 2
- LoRA dropout: 0.05
- Batch size: 2
- Gradient accumulation: 8
- Gradient checkpointing: Enabled
- Number of epochs: 3
- Context size: 3072
- Quantization: q4bit
Input type: template Output type: template
LoRA adapter for Mistral Instruct 7B v0.2
Training details
- Optimizer: awbn8
- Computational datatype: fp16
- Learning rate: 0.00005
- LoRA rank: 1024
- LoRA alpha multiplier: 2
- LoRA dropout: 0.05
- Batch size: 2
- Gradient accumulation: 8
- Gradient checkpointing: Enabled
- Number of epochs: 3
- Context size: 3072
- Quantization: q4bit
Input type: template Output type: template
LoRA adapter for Mistral Instruct 7B v0.2
Training details
- Optimizer: awbn8
- Computational datatype: fp16
- Learning rate: 0.00005
- LoRA rank: 1024
- LoRA alpha multiplier: 2
- LoRA dropout: 0.05
- Batch size: 2
- Gradient accumulation: 8
- Gradient checkpointing: Enabled
- Number of epochs: 3
- Context size: 3072
- Quantization: q4bit
Input type: template Output type: template
LoRA adapter for Mistral Instruct 7B v0.2
Training details
- Optimizer: awbn8
- Computational datatype: fp16
- Learning rate: 0.00005
- LoRA rank: 1024
- LoRA alpha multiplier: 2
- LoRA dropout: 0.05
- Batch size: 2
- Gradient accumulation: 8
- Gradient checkpointing: Enabled
- Number of epochs: 3
- Context size: 3072
- Quantization: q4bit
Input type: template Output type: template
LoRA adapter for Mistral Instruct 7B v0.2
Training details
- Optimizer: awbn8
- Computational datatype: fp16
- Learning rate: 0.00005
- LoRA rank: 1024
- LoRA alpha multiplier: 2
- LoRA dropout: 0.05
- Batch size: 2
- Gradient accumulation: 8
- Gradient checkpointing: Enabled
- Number of epochs: 3
- Context size: 3072
- Quantization: q4bit
Input type: template Output type: template
base_model: mistralai/Mistral-7B-Instruct-v0.2 library_name: peft
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Framework versions
- PEFT 0.11.2.dev0
- Created
- Aug 6, 2024
- Updated
- Aug 6, 2024