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Tukan-1.1B-Chat-v0.6_dpo

This model is a fine-tuned version of alexredna/Tukan-1.1B-Chat-v0.6 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6664
  • Rewards/chosen: -0.0698
  • Rewards/rejected: -0.1297
  • Rewards/accuracies: 0.6667
  • Rewards/margins: 0.0600
  • Logps/rejected: -364.0182
  • Logps/chosen: -408.6165
  • Logits/rejected: -2.1219
  • Logits/chosen: -2.2568

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: 3e-07
  • train_batch_size: 5
  • eval_batch_size: 3
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 160
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.6819 0.99 61 0.6804 -0.0465 -0.0746 0.6318 0.0281 -363.4672 -408.3842 -2.1356 -2.2671
0.6718 2.0 123 0.6719 -0.0689 -0.1170 0.6269 0.0482 -363.8911 -408.6075 -2.1242 -2.2588
0.6687 2.97 183 0.6664 -0.0698 -0.1297 0.6667 0.0600 -364.0182 -408.6165 -2.1219 -2.2568

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.0

Training procedure

The following bitsandbytes quantization config was used during training:

  • quant_method: bitsandbytes
  • load_in_8bit: False
  • load_in_4bit: True
  • llm_int8_threshold: 6.0
  • llm_int8_skip_modules: None
  • llm_int8_enable_fp32_cpu_offload: False
  • llm_int8_has_fp16_weight: False
  • bnb_4bit_quant_type: nf4
  • bnb_4bit_use_double_quant: False
  • bnb_4bit_compute_dtype: float16

Framework versions

  • PEFT 0.6.1
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