phi2-mentalchat16k / README.md
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Finetune on MentalChat16K - eval_loss: 0.7298
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metadata
library_name: peft
license: mit
base_model: microsoft/phi-2
tags:
  - generated_from_trainer
model-index:
  - name: phi2-mentalchat16k
    results: []

phi2-mentalchat16k

This model is a fine-tuned version of microsoft/phi-2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7112

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: 0.0002
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.8915 0.1496 100 0.8518
0.8464 0.2992 200 0.8102
0.7874 0.4488 300 0.7927
0.7999 0.5984 400 0.7814
0.7901 0.7479 500 0.7731
0.7801 0.8975 600 0.7647
0.7585 1.0471 700 0.7639
0.7592 1.1967 800 0.7576
0.7431 1.3463 900 0.7542
0.7555 1.4959 1000 0.7501
0.7354 1.6455 1100 0.7456
0.7281 1.7951 1200 0.7422
0.7312 1.9447 1300 0.7395
0.6984 2.0942 1400 0.7389
0.7037 2.2438 1500 0.7382
0.6913 2.3934 1600 0.7357
0.7229 2.5430 1700 0.7341
0.7095 2.6926 1800 0.7326
0.6994 2.8422 1900 0.7319
0.6995 2.9918 2000 0.7298
0.6887 3.1414 2100 0.7314
0.6712 3.2909 2200 0.7308
0.6867 3.4405 2300 0.7300
0.6817 3.5901 2400 0.7299
0.681 3.7397 2500 0.7296

Framework versions

  • PEFT 0.13.2
  • Transformers 4.46.3
  • Pytorch 2.4.1+cu118
  • Datasets 3.1.0
  • Tokenizers 0.20.3