vicuna-ul15-sft-full – AI Model by justinwangx | AlphaNeural AI

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justinwangx/
vicuna-ul15-sft-full

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text-generation

generated_from_trainer

autotrain_compatible

text-generation-inference

endpoints_compatible

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vicuna-ul15-sft-full

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.4380

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: 2e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 512
total_eval_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss
1.0541	0.68	14	1.0341
0.9708	1.71	29	1.0142
0.9142	2.68	43	1.0111
0.8637	3.71	58	1.0239
0.8091	4.68	72	1.0363
0.7516	5.71	87	1.0780
0.6884	6.68	101	1.0987
0.6309	7.71	116	1.1394
0.5696	8.68	130	1.1820
0.4752	9.71	145	1.2695
0.448	10.68	159	1.3109
0.3955	11.71	174	1.3877
0.3579	12.68	188	1.3923
0.3228	13.71	203	1.4064
0.2914	14.68	217	1.4377

Framework versions

Transformers 4.35.0
Pytorch 2.1.0a0+32f93b1
Datasets 2.14.6
Tokenizers 0.14.1