Phi-3.5-MultiCap-mt

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: 0.7569

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss
1.4288	0.1533	15	1.3449
1.0894	0.3065	30	1.1240
0.9541	0.4598	45	0.9830
0.9216	0.6130	60	0.8949
0.8675	0.7663	75	0.8414
0.8007	0.9195	90	0.8108
0.8205	1.0728	105	0.7919
0.7864	1.2261	120	0.7794
0.7983	1.3793	135	0.7705
0.7784	1.5326	150	0.7641
0.744	1.6858	165	0.7595
0.7765	1.8391	180	0.7569

Framework versions

• PEFT 0.12.0
• Transformers 4.44.2
• Pytorch 2.4.0+cu124
• Datasets 2.21.0
• Tokenizers 0.19.1