math-lora / README.md
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---
base_model: ISTA-DASLab/Meta-Llama-3-8B-Instruct-AQLM-2Bit-1x16
library_name: peft
tags:
- generated_from_trainer
model-index:
- name: math-lora
results: []
---
<!-- 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. -->
# math-lora
This model is a fine-tuned version of [ISTA-DASLab/Meta-Llama-3-8B-Instruct-AQLM-2Bit-1x16](https://huggingface.co/ISTA-DASLab/Meta-Llama-3-8B-Instruct-AQLM-2Bit-1x16) on the None dataset.
## 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: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 10000
### Framework versions
- PEFT 0.12.1.dev0
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1