QuantFactory/gemma-2-Ifable-9B-GGUF
This is quantized version of ifable/gemma-2-Ifable-9B created using llama.cpp
Original Model Card
ifable/gemma-2-Ifable-9B
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 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.3.0a0+ebedce2
- Datasets 2.20.0
- Tokenizers 0.19.1
We are looking for product manager and operations managers to build applications through our model, and also open for business cooperation, and also AI engineer to join us, contact with : [email protected]
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