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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-2e-07-0.5-linear-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-2e-07-0.5-linear-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: 0.6464
- Rewards/chosen: 0.4833
- Rewards/rejected: -0.1353
- Rewards/accuracies: 0.3710
- Rewards/margins: 0.6186
- Logps/rejected: -81.3989
- Logps/chosen: -73.5245
- Logits/rejected: -2.5552
- Logits/chosen: -2.5716
## 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: 2e-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: linear
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6562 | 0.3484 | 100 | 0.6328 | 0.6802 | 0.3841 | 0.3552 | 0.2961 | -80.3602 | -73.1308 | -2.5405 | -2.5565 |
| 0.6601 | 0.6969 | 200 | 0.6410 | 0.2989 | -0.0897 | 0.3452 | 0.3887 | -81.3078 | -73.8934 | -2.5169 | -2.5332 |
| 0.4195 | 1.0453 | 300 | 0.6371 | 0.6242 | 0.1593 | 0.3532 | 0.4648 | -80.8097 | -73.2429 | -2.5193 | -2.5354 |
| 0.3956 | 1.3937 | 400 | 0.6460 | 0.4324 | -0.1472 | 0.3631 | 0.5796 | -81.4227 | -73.6264 | -2.5378 | -2.5541 |
| 0.3945 | 1.7422 | 500 | 0.6465 | 0.3072 | -0.2969 | 0.3710 | 0.6040 | -81.7221 | -73.8769 | -2.5543 | -2.5709 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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