llama-3-8b-base-sft-ultrachat-8xh200 – AI Model by W-61 | AlphaNeural AI

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W-61/
llama-3-8b-base-sft-ultrachat-8xh200

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text-generation

alignment-handbook

generated_from_trainer

HuggingFaceH4/ultrachat_200k

meta-llama/Meta-Llama-3-8B

text-generation-inference

endpoints_compatible

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llama-3-8b-base-sft-ultrachat-8xh200-20260410-113950

This model is a fine-tuned version of /scratch/feng.yulu/dynamic-dpo-v4/base_models/Meta-Llama-3-8B on the HuggingFaceH4/ultrachat_200k dataset. It achieves the following results on the evaluation set:

Loss: 1.0705

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: 16
eval_batch_size: 16
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 128
total_eval_batch_size: 128
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
1.1453	0.2137	200	1.1343
1.0929	0.4274	400	1.1096
1.0808	0.6410	600	1.0848
1.0529	0.8547	800	1.0705

Framework versions

Transformers 4.51.0
Pytorch 2.3.1+cu121
Datasets 2.21.0
Tokenizers 0.21.4