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---
license: other
base_model: meta-llama/Meta-Llama-3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: C017_random_sample_llama3-8b-base_instruct_20240504_182259
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. -->
# C017_random_sample_llama3-8b-base_instruct_20240504_182259
This model is a fine-tuned version of [./output/training_results/C017_random_sample_llama3-8b-base_pretrain_20240504_182259/](https://huggingface.co/./output/training_results/C017_random_sample_llama3-8b-base_pretrain_20240504_182259/) on the instructions_curated dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8518
## 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: 1.5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_steps: 20
- num_epochs: 4.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8222 | 0.4167 | 20 | 0.8593 |
| 0.8014 | 0.8333 | 40 | 0.8518 |
| 0.4422 | 1.25 | 60 | 0.8722 |
| 0.4551 | 1.6667 | 80 | 0.8555 |
| 0.3806 | 2.0833 | 100 | 0.8530 |
| 0.4011 | 2.5 | 120 | 0.8577 |
| 0.37 | 2.9167 | 140 | 0.8622 |
| 0.3626 | 3.3333 | 160 | 0.8659 |
| 0.3708 | 3.75 | 180 | 0.8687 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1
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