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---
license: llama3.1
base_model: NousResearch/Meta-Llama-3.1-8B-Instruct
tags:
- generated_from_trainer
model-index:
- name: Llama-3.1-8B-Instruct-EI1-120K-fix-32gpus
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. -->
# Llama-3.1-8B-Instruct-EI1-120K-fix-32gpus
This model is a fine-tuned version of [NousResearch/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3.1-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4036
## 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: 6e-06
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- total_train_batch_size: 64
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log | 0.2924 | 100 | 0.5279 |
| No log | 0.5848 | 200 | 0.4631 |
| No log | 0.8772 | 300 | 0.4304 |
| No log | 1.1696 | 400 | 0.4153 |
| 0.4771 | 1.4620 | 500 | 0.4072 |
| 0.4771 | 1.7544 | 600 | 0.4036 |
### Framework versions
- Transformers 4.43.4
- Pytorch 2.4.0+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
|