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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-6e-07-0.53-polynomial-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-6e-07-0.53-polynomial-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: 0.8595
- Rewards/chosen: 1.8502
- Rewards/rejected: 0.6070
- Rewards/accuracies: 0.3393
- Rewards/margins: 1.2433
- Logps/rejected: -79.9832
- Logps/chosen: -71.0003
- Logits/rejected: -2.6929
- Logits/chosen: -2.7082
## 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: 6e-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: polynomial
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7136 | 0.3484 | 100 | 0.7109 | 1.4011 | 0.8625 | 0.3512 | 0.5386 | -79.5010 | -71.8476 | -2.5458 | -2.5618 |
| 0.7461 | 0.6969 | 200 | 0.7643 | 1.0640 | 0.3687 | 0.3274 | 0.6952 | -80.4327 | -72.4838 | -2.5601 | -2.5759 |
| 0.3949 | 1.0453 | 300 | 0.7875 | 0.2070 | -0.6350 | 0.3472 | 0.8420 | -82.3265 | -74.1006 | -2.6135 | -2.6292 |
| 0.3838 | 1.3937 | 400 | 0.8714 | 0.4396 | -0.7042 | 0.3294 | 1.1438 | -82.4571 | -73.6618 | -2.6266 | -2.6422 |
| 0.371 | 1.7422 | 500 | 0.8639 | 0.6923 | -0.5434 | 0.3393 | 1.2357 | -82.1536 | -73.1851 | -2.6910 | -2.7068 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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