llm-wizard/
llama381binstruct_summarize

Name: llama381binstruct_summarize
Availability: InStock

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generated_from_trainer

generator

NousResearch/Meta-Llama-3.1-8B-Instruct

adapter

llama3.1

GPU deploy isn't supported for this model type.

llama381binstruct_summarize

This model is a fine-tuned version of NousResearch/Meta-Llama-3.1-8B-Instruct on the generator dataset. It achieves the following results on the evaluation set:

Loss: 2.7355

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: 1
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 30
training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss
1.6918	1.3158	25	1.6215
0.6871	2.6316	50	1.6851
0.3017	3.9474	75	1.8694
0.1642	5.2632	100	2.2410
0.0667	6.5789	125	2.2806
0.0352	7.8947	150	2.4889
0.0292	9.2105	175	2.5073
0.0117	10.5263	200	2.5430
0.0111	11.8421	225	2.5160
0.0101	13.1579	250	2.5102
0.0083	14.4737	275	2.5176
0.0033	15.7895	300	2.5635
0.0028	17.1053	325	2.6311
0.0022	18.4211	350	2.6684
0.0016	19.7368	375	2.6933
0.0021	21.0526	400	2.7102
0.0019	22.3684	425	2.7220
0.0016	23.6842	450	2.7295
0.0018	25.0	475	2.7339
0.0017	26.3158	500	2.7355

Framework versions

PEFT 0.12.0
Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 3.0.0
Tokenizers 0.19.1

llm-wizard/llama381binstruct_summarize

llama381binstruct_summarize

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

llm-wizard/
llama381binstruct_summarize