---

pipeline_tag: text-generation
base_model: gemma-2-Ifable-9B
library_name: transformers

---

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# QuantFactory/gemma-2-Ifable-9B-GGUF
This is quantized version of [ifable/gemma-2-Ifable-9B](https://huggingface.co/ifable/gemma-2-Ifable-9B) created using llama.cpp

# Original Model Card

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 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 : contact@ifable.ai