llama-lora-Atayal-summarization – AI Model by aslinguist | AlphaNeural AI

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llama-lora-Atayal-summarization

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meta-llama/Llama-3.1-8B-Instruct

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llama-lora-Atayal-summarization

This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7728

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: 0.001
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
3.5911	1.0	42	0.8258
2.9427	2.0	84	0.7557
2.8432	3.0	126	0.7325
2.3331	4.0	168	0.7204
1.684	5.0	210	0.7282
1.5264	6.0	252	0.7463
1.3946	7.0	294	0.7728

Framework versions

PEFT 0.15.0
Transformers 4.51.2
Pytorch 2.2.2+cu118
Datasets 3.5.0
Tokenizers 0.21.1