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---
library_name: transformers
license: llama3.1
base_model: meta-llama/Llama-3.1-8B
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
model-index:
- name: zephyr-8b-sft-full
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. -->
# zephyr-8b-sft-full
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) on the HuggingFaceH4/ultrachat_200k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0747
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.103 | 0.1052 | 100 | 1.0989 |
| 1.0867 | 0.2103 | 200 | 1.0966 |
| 1.111 | 0.3155 | 300 | 1.1012 |
| 1.0974 | 0.4206 | 400 | 1.0966 |
| 1.0898 | 0.5258 | 500 | 1.0920 |
| 1.0749 | 0.6309 | 600 | 1.0876 |
| 1.0847 | 0.7361 | 700 | 1.0831 |
| 1.0749 | 0.8412 | 800 | 1.0778 |
| 1.055 | 0.9464 | 900 | 1.0720 |
| 0.9184 | 1.0515 | 1000 | 1.0817 |
| 0.8955 | 1.1567 | 1100 | 1.0779 |
| 0.914 | 1.2618 | 1200 | 1.0758 |
| 0.9098 | 1.3670 | 1300 | 1.0698 |
| 0.9126 | 1.4721 | 1400 | 1.0667 |
| 0.9032 | 1.5773 | 1500 | 1.0604 |
| 0.8882 | 1.6824 | 1600 | 1.0546 |
| 0.8847 | 1.7876 | 1700 | 1.0490 |
| 0.8831 | 1.8927 | 1800 | 1.0455 |
| 0.8781 | 1.9979 | 1900 | 1.0413 |
| 0.7197 | 2.1030 | 2000 | 1.0822 |
| 0.7137 | 2.2082 | 2100 | 1.0841 |
| 0.7115 | 2.3134 | 2200 | 1.0800 |
| 0.7178 | 2.4185 | 2300 | 1.0789 |
| 0.7063 | 2.5237 | 2400 | 1.0777 |
| 0.6964 | 2.6288 | 2500 | 1.0755 |
| 0.7121 | 2.7340 | 2600 | 1.0742 |
| 0.7049 | 2.8391 | 2700 | 1.0748 |
| 0.7024 | 2.9443 | 2800 | 1.0747 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.2.2+rocm5.7
- Datasets 3.2.0
- Tokenizers 0.20.3
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