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---
library_name: transformers
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: openmathinstruct2-llama-3.1-8B-Instruct-lr5-ep2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# openmathinstruct2-llama-3.1-8B-Instruct-lr5-ep2
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the openmathinstruct2_cot_20k_train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7634
## 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-05
- 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: 2.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8177 | 0.4808 | 500 | 0.7823 |
| 0.7708 | 0.9615 | 1000 | 0.7572 |
| 0.5513 | 1.4423 | 1500 | 0.7693 |
| 0.5059 | 1.9231 | 2000 | 0.7637 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.1