Phi-3.5-MultiCap-tool-embedding-3 – AI Model by sofyc | AlphaNeural AI

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sofyc/
Phi-3.5-MultiCap-tool-embedding-3

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microsoft/Phi-3.5-mini-instruct

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Phi-3.5-MultiCap-tool-embedding-3

This model is a fine-tuned version of microsoft/Phi-3.5-mini-instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5221

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: 16
eval_batch_size: 16
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: linear
lr_scheduler_warmup_ratio: 0.03
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.8799	0.2256	50	0.8806
0.6125	0.4512	100	0.6177
0.5659	0.6768	150	0.5733
0.6125	0.9024	200	0.5550
0.5402	1.1280	250	0.5448
0.5299	1.3536	300	0.5378
0.4997	1.5792	350	0.5331
0.549	1.8049	400	0.5296
0.5361	2.0305	450	0.5268
0.4821	2.2561	500	0.5249
0.5274	2.4817	550	0.5234
0.5344	2.7073	600	0.5227
0.546	2.9329	650	0.5221

Framework versions

PEFT 0.12.0
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1