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---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- sablo/HelpSteer_binarized
base_model: sablo/sablo-pebble-mistral
model-index:
- name: sablo-pebble-mistral-dpo-lora-HelpSteer_binarized
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. -->
# sablo-pebble-mistral-dpo-lora-HelpSteer_binarized
This model is a fine-tuned version of [sablo/sablo-pebble-mistral](https://huggingface.co/sablo/sablo-pebble-mistral) on the sablo/HelpSteer_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5371
- Rewards/chosen: -0.9335
- Rewards/rejected: -1.6455
- Rewards/accuracies: 0.7264
- Rewards/margins: 0.7121
- Logps/rejected: -298.0735
- Logps/chosen: -253.4149
- Logits/rejected: -2.4554
- Logits/chosen: -2.5093
## 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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6874 | 0.1 | 100 | 0.6892 | 0.0213 | 0.0133 | 0.6698 | 0.0080 | -132.1924 | -157.9395 | -2.4463 | -2.4843 |
| 0.6592 | 0.2 | 200 | 0.6594 | 0.0055 | -0.0704 | 0.6698 | 0.0759 | -140.5588 | -159.5180 | -2.4922 | -2.5370 |
| 0.5451 | 0.3 | 300 | 0.5867 | -0.4490 | -0.7587 | 0.6863 | 0.3097 | -209.3938 | -204.9713 | -2.5128 | -2.5620 |
| 0.4933 | 0.39 | 400 | 0.5591 | -0.6060 | -1.1029 | 0.7146 | 0.4968 | -243.8062 | -220.6713 | -2.4868 | -2.5386 |
| 0.5271 | 0.49 | 500 | 0.5488 | -0.6712 | -1.2738 | 0.7193 | 0.6026 | -260.8958 | -227.1889 | -2.4784 | -2.5312 |
| 0.4594 | 0.59 | 600 | 0.5418 | -0.7977 | -1.4672 | 0.7311 | 0.6695 | -280.2420 | -239.8430 | -2.4672 | -2.5200 |
| 0.5444 | 0.69 | 700 | 0.5358 | -0.7688 | -1.4528 | 0.7335 | 0.6840 | -278.8014 | -236.9531 | -2.4594 | -2.5127 |
| 0.5755 | 0.79 | 800 | 0.5405 | -1.0672 | -1.7631 | 0.7311 | 0.6959 | -309.8293 | -266.7906 | -2.4585 | -2.5118 |
| 0.5495 | 0.89 | 900 | 0.5371 | -0.9321 | -1.6450 | 0.7288 | 0.7129 | -298.0242 | -253.2804 | -2.4558 | -2.5096 |
| 0.5948 | 0.98 | 1000 | 0.5371 | -0.9335 | -1.6455 | 0.7264 | 0.7121 | -298.0735 | -253.4149 | -2.4554 | -2.5093 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.15.0 |