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cshbi/
fine_tune_output_eie_3.1

generated_from_trainer

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

adapter

llama3.1

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fine_tune_output_eie_3.1

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: 0.0554

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: 2
eval_batch_size: 2
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: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 100

Training results

Training Loss	Epoch	Step	Validation Loss
3.4001	0.0175	10	3.0656
0.2084	0.0351	20	0.1816
0.2639	0.0526	30	0.0741
0.1448	0.0702	40	0.1223
0.1068	0.0877	50	0.2702
0.1196	0.1053	60	0.0654
0.1132	0.1228	70	0.0576
0.0321	0.1404	80	0.0822
0.0695	0.1579	90	0.0670
0.0143	0.1754	100	0.0554

Framework versions

PEFT 0.10.0
Transformers 4.44.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.19.1

cshbi/fine_tune_output_eie_3.1

fine_tune_output_eie_3.1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

cshbi/
fine_tune_output_eie_3.1