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HusnainM7/
nRich-SLM-2

Name: nRich-SLM-2
Availability: InStock

generated_from_trainer

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

adapter

llama3.1

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new_intruct_llama

This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.0435

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: 2
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.4416	0.2584	50	1.4172
1.2754	0.5168	100	1.2522
1.191	0.7752	150	1.1805
1.1082	1.0336	200	1.1388
1.1026	1.2920	250	1.1138
1.0596	1.5504	300	1.0915
1.0589	1.8088	350	1.0756
0.9874	2.0672	400	1.0660
1.0128	2.3256	450	1.0569
0.9887	2.5840	500	1.0494
0.9708	2.8424	550	1.0435

Framework versions

PEFT 0.11.0
Transformers 4.44.0
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.19.1

HusnainM7/nRich-SLM-2

new_intruct_llama

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

HusnainM7/
nRich-SLM-2