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---
base_model: ondevicellm/tinyllama_mole_sft_ultrachat_ep3
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: tinyllama_mole_dpo_ep3
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. -->
# tinyllama_mole_dpo_ep3
This model is a fine-tuned version of [ondevicellm/tinyllama_mole_sft_ultrachat_ep3](https://huggingface.co/ondevicellm/tinyllama_mole_sft_ultrachat_ep3) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6285
- Rewards/chosen: -0.3050
- Rewards/rejected: -0.5353
- Rewards/accuracies: 0.6806
- Rewards/margins: 0.2302
- Logps/rejected: -354.2071
- Logps/chosen: -373.1399
- Logits/rejected: -1.6731
- Logits/chosen: -1.8041
## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6896 | 0.1 | 100 | 0.6899 | 0.0064 | -0.0013 | 0.6448 | 0.0076 | -300.8089 | -342.0017 | -1.7574 | -1.8918 |
| 0.6762 | 0.21 | 200 | 0.6756 | -0.0293 | -0.0716 | 0.6627 | 0.0423 | -307.8423 | -345.5688 | -1.7501 | -1.8839 |
| 0.6499 | 0.31 | 300 | 0.6587 | -0.0875 | -0.1813 | 0.6687 | 0.0938 | -318.8118 | -351.3895 | -1.7358 | -1.8688 |
| 0.6374 | 0.42 | 400 | 0.6451 | -0.1726 | -0.3218 | 0.6746 | 0.1493 | -332.8632 | -359.8953 | -1.7164 | -1.8482 |
| 0.6348 | 0.52 | 500 | 0.6377 | -0.2696 | -0.4550 | 0.6647 | 0.1854 | -346.1808 | -369.6013 | -1.6884 | -1.8208 |
| 0.6308 | 0.63 | 600 | 0.6333 | -0.2783 | -0.4815 | 0.6726 | 0.2032 | -348.8291 | -370.4673 | -1.6965 | -1.8269 |
| 0.62 | 0.73 | 700 | 0.6312 | -0.2323 | -0.4505 | 0.6806 | 0.2182 | -345.7306 | -365.8656 | -1.6841 | -1.8149 |
| 0.6055 | 0.84 | 800 | 0.6287 | -0.2877 | -0.5169 | 0.6865 | 0.2292 | -352.3697 | -371.4099 | -1.6793 | -1.8099 |
| 0.6357 | 0.94 | 900 | 0.6285 | -0.3050 | -0.5353 | 0.6806 | 0.2302 | -354.2071 | -373.1399 | -1.6731 | -1.8041 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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