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dwb2023/
llama38binstruct_summarize_jun14

Name: llama38binstruct_summarize_jun14
Availability: InStock

generated_from_trainer

generator

NousResearch/Meta-Llama-3-8B-Instruct

adapter

other

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llama38binstruct_summarize_jun14

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

Loss: 1.5923

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: constant
lr_scheduler_warmup_steps: 0.03
training_steps: 100

Training results

Training Loss	Epoch	Step	Validation Loss
0.0677	1.3889	25	1.4830
0.0299	2.7778	50	1.5549
0.0295	4.1667	75	1.5254
0.0167	5.5556	100	1.5923

Framework versions

PEFT 0.11.1
Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

dwb2023/llama38binstruct_summarize_jun14

llama38binstruct_summarize_jun14

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

dwb2023/
llama38binstruct_summarize_jun14