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---
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-align-scan-7e-07-0.99-cosine-2.0
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. -->
# zephyr-7b-align-scan-7e-07-0.99-cosine-2.0
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1727
- Rewards/chosen: 2.6978
- Rewards/rejected: 0.6816
- Rewards/accuracies: 0.3472
- Rewards/margins: 2.0163
- Logps/rejected: -80.4399
- Logps/chosen: -71.7662
- Logits/rejected: -2.6444
- Logits/chosen: -2.6613
## 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: 7e-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_ratio: 0.1
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.9118 | 0.3484 | 100 | 0.8952 | 1.8796 | 1.1355 | 0.3353 | 0.7441 | -79.9814 | -72.5926 | -2.5564 | -2.5727 |
| 0.9553 | 0.6969 | 200 | 1.0700 | 2.5989 | 1.4006 | 0.3413 | 1.1983 | -79.7136 | -71.8661 | -2.5726 | -2.5893 |
| 0.4066 | 1.0453 | 300 | 1.0729 | 2.3164 | 0.9125 | 0.3433 | 1.4038 | -80.2066 | -72.1515 | -2.5962 | -2.6126 |
| 0.3805 | 1.3937 | 400 | 1.1546 | 2.9774 | 1.1937 | 0.3373 | 1.7837 | -79.9225 | -71.4837 | -2.6247 | -2.6413 |
| 0.3975 | 1.7422 | 500 | 1.1824 | 2.5463 | 0.5342 | 0.3452 | 2.0120 | -80.5887 | -71.9193 | -2.6463 | -2.6632 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1