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---
license: other
base_model: lewtun/gemma-7b-sft-full-deita-10k-v0
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- argilla/dpo-mix-7k
model-index:
- name: gemma-7b-dpo-full-mix1-beta-0.05-epoch-2
results: []
---
<!-- 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. -->
# gemma-7b-dpo-full-mix1-beta-0.05-epoch-2
This model is a fine-tuned version of [lewtun/gemma-7b-sft-full-deita-10k-v0](https://huggingface.co/lewtun/gemma-7b-sft-full-deita-10k-v0) on the argilla/dpo-mix-7k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4897
- Rewards/chosen: -2.0476
- Rewards/rejected: -3.4508
- Rewards/accuracies: 0.7083
- Rewards/margins: 1.4032
- Logps/rejected: -520.5655
- Logps/chosen: -494.3556
- Logits/rejected: 93.1721
- Logits/chosen: 99.2168
## 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: 5e-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.193 | 1.9 | 100 | 0.4773 | -2.0019 | -3.4640 | 0.7292 | 1.4620 | -520.8292 | -493.4434 | 93.2355 | 99.2919 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1
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