outputs – AI Model by lbruderer | AlphaNeural AI

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google/gemma-2b-it

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outputs

This model is a fine-tuned version of google/gemma-2b-it on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.0962

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
3.5696	0.93	7	2.3790
1.7335	2.0	15	1.6733
1.5583	2.93	22	1.5446
1.1347	4.0	30	1.5097
1.0502	4.93	37	1.5663
0.7217	6.0	45	1.6769
0.6408	6.93	52	1.8386
0.43	8.0	60	1.9674
0.391	8.93	67	2.0831
0.2893	9.33	70	2.0962

Framework versions

PEFT 0.9.0
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2