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dhanishetty/
llama_qLoRA_Adapters_2

Name: llama_qLoRA_Adapters_2
Availability: InStock

generated_from_trainer

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

adapter

llama3

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llama-qLoRA

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.9238

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: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
1.2796	0.2022	100	1.2957
1.132	0.4044	200	1.1329
1.0712	0.6067	300	1.0974
1.0711	0.8089	400	1.0586
0.9632	1.0111	500	1.0059
0.9462	1.2133	600	0.9607
0.965	1.4156	700	0.9520
0.9302	1.6178	800	0.9470
0.9227	1.8200	900	0.9418
0.9023	2.0222	1000	0.9375
0.9093	2.2245	1100	0.9339
0.9202	2.4267	1200	0.9300
0.9061	2.6289	1300	0.9263
0.915	2.8311	1400	0.9238

Framework versions

PEFT 0.11.1
Transformers 4.42.4
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

dhanishetty/llama_qLoRA_Adapters_2

llama-qLoRA

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

dhanishetty/
llama_qLoRA_Adapters_2