GREEN-RadPhi2 – AI Model by StanfordAIMI | AlphaNeural AI

You can deploy this model and start earning money today!

StanfordAIMI/
GREEN-RadPhi2

like

0

text-generation

generated_from_trainer

StanfordAIMI/RadPhi-2

autotrain_compatible

text-generation-inference

endpoints_compatible

Views

No views yet

outputs_20240325

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

Loss: 0.0816

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: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 32
total_train_batch_size: 2048
total_eval_batch_size: 64
optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.05
num_epochs: 12.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.1831	0.64	25	0.1257
0.1239	1.28	50	0.1044
0.108	1.92	75	0.0995
0.0976	2.56	100	0.0978
0.094	3.2	125	0.0886
0.0828	3.84	150	0.0893
0.078	4.48	175	0.0907
0.0767	5.12	200	0.0866
0.0697	5.76	225	0.0840
0.0646	6.39	250	0.0819
0.0594	7.03	275	0.0795
0.052	7.67	300	0.0795
0.0478	8.31	325	0.0803
0.0447	8.95	350	0.0786
0.0392	9.59	375	0.0800
0.038	10.23	400	0.0813
0.0357	10.87	425	0.0810
0.035	11.51	450	0.0816

Framework versions

Transformers 4.38.1
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2