my-llama – AI Model by SherifEssam02 | AlphaNeural AI

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SherifEssam02/
my-llama

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distilbert/distilbert-base-uncased

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my-llama

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2818
F1: 0.932

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant
training_steps: 140

Training results

Training Loss	Epoch	Step	Validation Loss	F1
1.3256	0.0889	20	1.2740	0.39
1.2235	0.1778	40	1.1644	0.39
1.0825	0.2667	60	0.9224	0.7
0.7699	0.3556	80	0.6128	0.852
0.5297	0.4444	100	0.4111	0.923
0.4467	0.5333	120	0.3114	0.93
0.3814	0.6222	140	0.2818	0.932

Framework versions

PEFT 0.15.0
Transformers 4.50.1
Pytorch 2.5.1+cu121
Datasets 3.4.1
Tokenizers 0.21.0