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Model: ifable/gemma-2-Ifable-9B Source: Original Platform
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README.md
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---
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license: gemma
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library_name: transformers
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datasets:
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- jondurbin/gutenberg-dpo-v0.1
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# ifable/gemma-2-Ifable-9B
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This model ranked first on the Creative Writing Benchmark (https://eqbench.com/creative_writing.html) on September 10, 2024
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## Training and evaluation data
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- Gutenberg: https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1
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- Carefully curated proprietary creative writing dataset
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## Training procedure
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Training method: SimPO (GitHub - princeton-nlp/SimPO: SimPO: Simple Preference Optimization with a Reference-Free Reward)
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It achieves the following results on the evaluation set:
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- Loss: 1.0163
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- Rewards/chosen: -21.6822
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- Rewards/rejected: -47.8754
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- Rewards/accuracies: 0.9167
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- Rewards/margins: 26.1931
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- Logps/rejected: -4.7875
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- Logps/chosen: -2.1682
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- Logits/rejected: -17.0475
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- Logits/chosen: -12.0041
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 8e-07
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 128
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- total_eval_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Sft Loss |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
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| 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 |
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### Framework versions
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- Transformers 4.43.4
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- Pytorch 2.3.0a0+ebedce2
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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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
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