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metadata
library_name: transformers
license: other
base_model: hon9kon9ize/CantoneseLLM-7B-sft
tags:
  - llama-factory
  - full
  - generated_from_trainer
model-index:
  - name: CantoneseLLMChat-v1.0
    results: []

CantoneseLLMChat-v1.0

This model is a fine-tuned version of hon9kon9ize/CantoneseLLM-7B-sft on the dpo_v1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3170
  • Rewards/chosen: -0.7307
  • Rewards/rejected: -3.1239
  • Rewards/accuracies: 0.8464
  • Rewards/margins: 2.3931
  • Logps/rejected: -226.0627
  • Logps/chosen: -191.7517
  • Logits/rejected: -1.5777
  • Logits/chosen: -1.5363

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: 5e-06
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.0835 1.3495 500 0.3282 -0.6181 -2.8043 0.8494 2.1862 -222.8677 -190.6253 -1.5563 -1.5215
0.1151 2.6991 1000 0.3186 -0.7277 -3.1230 0.8524 2.3953 -226.0546 -191.7211 -1.5777 -1.5363

Framework versions

  • Transformers 4.45.0
  • Pytorch 2.4.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.20.0