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metadata
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: Phi-3.5-MultiCap-tool-embedding-pos
    results: []

Phi-3.5-MultiCap-tool-embedding-pos

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: 0.5085

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
0.6807 0.2256 50 0.6677
0.5536 0.4512 100 0.5629
0.5297 0.6768 150 0.5375
0.5759 0.9024 200 0.5250
0.5068 1.1280 250 0.5175
0.4954 1.3536 300 0.5129
0.4675 1.5792 350 0.5101
0.5153 1.8049 400 0.5085

Framework versions

  • PEFT 0.12.0
  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1