Llama-360M-finaltest – AI Model by ninagroot | AlphaNeural AI

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ninagroot/
Llama-360M-finaltest

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text-generation

generated_from_trainer

autotrain_compatible

text-generation-inference

endpoints_compatible

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Llama-360M

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.8245

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: 0.0003
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 300
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
8.6417	1.0	3	8.5751
8.3908	2.0	6	8.3473
7.9583	3.0	9	7.9814
7.3598	4.0	12	7.5011
6.7468	5.0	15	6.9942
6.3345	6.0	18	6.6309
6.0489	7.0	21	6.3987
5.9651	8.0	24	6.2101
5.7683	9.0	27	5.9691
5.3051	10.0	30	5.5791
4.6791	11.0	33	5.1445
4.3962	12.0	36	4.8859
4.0007	13.0	39	4.7013
3.9473	14.0	42	4.4994
3.5486	15.0	45	4.3178
3.3243	16.0	48	4.1587
3.1305	17.0	51	4.0505
2.8703	18.0	54	3.9467
2.7661	19.0	57	3.8780
2.7976	20.0	60	3.8245

Framework versions

Transformers 4.39.1
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.0