shawgpt-ft / README.md
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thomnis/Mistral-7B-Instruct-v0.2-GPTQ-LoRA-shawgpt-ft
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metadata
base_model: mistralai/Mistral-7B-Instruct-v0.3
library_name: peft
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: shawgpt-ft
    results: []

shawgpt-ft

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5866

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: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
4.586 0.9231 3 4.0840
4.5013 1.8462 6 3.6804
3.4295 2.7692 9 2.6498
1.7662 4.0 13 1.7049
1.6274 4.9231 16 1.4525
1.3983 5.8462 19 1.3957
1.2807 6.7692 22 1.3583
0.9365 8.0 26 1.3325
1.1829 8.9231 29 1.3339
1.0945 9.8462 32 1.3330
1.0448 10.7692 35 1.3496
0.7014 12.0 39 1.3455
0.8887 12.9231 42 1.3879
0.8145 13.8462 45 1.4225
0.7586 14.7692 48 1.4449
0.5382 16.0 52 1.5154
0.6563 16.9231 55 1.4966
0.6154 17.8462 58 1.5442
0.4083 18.4615 60 1.5866

Framework versions

  • PEFT 0.13.2
  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1