openmathinstruct2-llama-3.1-8B-Instruct-lr7-ep1
This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the openmathinstruct2_cot_20k_train dataset. It achieves the following results on the evaluation set:
- Loss: 0.7567
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: 1e-07
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
Training results
Framework versions
- Transformers 4.45.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.1
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Model tree for jiawei1018/openmathinstruct2-llama-3.1-8B-Instruct-lr7-ep1
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct