duyntnet/gemma-2-Ifable-9B-imatrix-GGUF

Quantizations of https://huggingface.co/ifable/gemma-2-Ifable-9B

Inference Clients/UIs

• llama.cpp
• KoboldCPP
• ollama
• text-generation-webui
• jan
• GPT4All

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From original readme

This model ranked first on the Creative Writing Benchmark (https://eqbench.com/creative_writing.html) on September 10, 2024

Training and evaluation data

• Gutenberg: https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1
• Carefully curated proprietary creative writing dataset

Training procedure

Training method: SimPO (GitHub - princeton-nlp/SimPO: SimPO: Simple Preference Optimization with a Reference-Free Reward)

It achieves the following results on the evaluation set:

• Loss: 1.0163
• Rewards/chosen: -21.6822
• Rewards/rejected: -47.8754
• Rewards/accuracies: 0.9167
• Rewards/margins: 26.1931
• Logps/rejected: -4.7875
• Logps/chosen: -2.1682
• Logits/rejected: -17.0475
• Logits/chosen: -12.0041

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 8e-07
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 16
• total_train_batch_size: 128
• total_eval_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: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen	Sft Loss
1.4444	0.9807	35	1.0163	-21.6822	-47.8754	0.9167	26.1931	-4.7875	-2.1682	-17.0475	-12.0041	0.0184