shawgpt-ft – AI Model by hj21 | AlphaNeural AI

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hj21/
shawgpt-ft

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meta-llama/Llama-3.2-1B

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shawgpt-ft

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.9054

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: 0.0002
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
4.0948	0.9231	3	3.5602
3.989	1.8462	6	3.4689
3.8695	2.7692	9	3.3643
2.7993	4.0	13	3.2266
3.6082	4.9231	16	3.1340
3.4814	5.8462	19	3.0544
3.3948	6.7692	22	2.9899
2.4744	8.0	26	2.9295
3.2539	8.9231	29	2.9079
2.2491	9.2308	30	2.9054

Framework versions

PEFT 0.13.2
Transformers 4.44.2
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.19.1