llama3-8B_MT – AI Model by rishavranaut | AlphaNeural AI

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rishavranaut/
llama3-8B_MT

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

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llama3-8B_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: 0.6988
Accuracy: 0.7817
Precision: 0.7394
Recall: 0.87
F1 score: 0.7994

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
0.7787	0.5	200	0.7533	0.7605	0.7390	0.7833	0.6041
0.5489	1.0	400	0.73	0.7484	0.7006	0.8033	0.5793
0.3894	1.5	600	0.6433	0.7214	0.5919	0.9233	0.7408
0.3638	2.0	800	0.7533	0.7817	0.7011	0.8833	0.5249
0.2665	2.5	1000	0.4719	0.8	0.7744	0.8467	0.8089
0.2587	3.0	1200	0.4709	0.7917	0.7660	0.84	0.8013
0.1716	3.5	1400	0.4906	0.8083	0.7955	0.83	0.8124
0.1672	4.0	1600	0.8441	0.7083	0.6478	0.9133	0.7580
0.0866	4.5	1800	0.6659	0.7917	0.7522	0.87	0.8068
0.0822	5.0	2000	0.6988	0.7817	0.7394	0.87	0.7994

Framework versions

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