Llama3_8B_final_MT – AI Model by rishavranaut | AlphaNeural AI

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rishavranaut/
Llama3_8B_final_MT

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

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Llama3_8B_final_MT

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6495
Accuracy: 0.7983
Precision: 0.8076
Recall: 0.7833
F1 score: 0.7953

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: 0.0001
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Accuracy	F1 score	Precision	Recall	Validation Loss
0.6898	0.5	200	0.745	0.7339	0.7673	0.7033	0.6158
0.5331	1.0	400	0.7817	0.7698	0.8141	0.73	0.5279
0.3824	1.5	600	0.7667	0.7846	0.7286	0.85	0.5694
0.3539	2.0	800	0.4800	0.805	0.8427	0.75	0.7937
0.2684	2.5	1000	0.5545	0.795	0.7864	0.81	0.7980
0.247	3.0	1200	0.5031	0.8233	0.8540	0.78	0.8153
0.164	3.5	1400	0.5347	0.8183	0.8687	0.75	0.8050
0.1628	4.0	1600	0.5893	0.8	0.7903	0.8167	0.8033
0.0864	4.5	1800	0.6370	0.81	0.8142	0.8033	0.8087
0.0802	5.0	2000	0.6495	0.7983	0.8076	0.7833	0.7953

Framework versions

PEFT 0.11.1
Transformers 4.44.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1