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---
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- trl
- dpo
- alignment-handbook
- generated_from_trainer
model-index:
- name: zephyr-7b-align-scan
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
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on an unknown dataset.
It achieves the following results on the evaluation set:
- Logits/chosen: 0.4326
- Logits/rejected: 0.9106
- Logps/chosen: -136.2882
- Logps/rejected: -189.5506
- Loss: 0.5958
- Rewards/accuracies: 0.3710
- Rewards/chosen: -0.6180
- Rewards/margins: 0.4663
- Rewards/rejected: -1.0842
## 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_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:------:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.6719 | 0.1047 | 100 | -2.3487 | -2.3310 | -73.2865 | -85.4479 | 0.6687 | 0.3274 | 0.0120 | 0.0552 | -0.0432 |
| 0.6488 | 0.2093 | 200 | -1.2584 | -1.2396 | -102.5743 | -130.3725 | 0.6348 | 0.3373 | -0.2808 | 0.2116 | -0.4924 |
| 0.6331 | 0.3140 | 300 | -1.1873 | -1.0320 | -120.1307 | -157.0977 | 0.6195 | 0.3452 | -0.4564 | 0.3033 | -0.7597 |
| 0.6321 | 0.4186 | 400 | 0.0335 | 0.3728 | -146.9637 | -190.2757 | 0.6099 | 0.3631 | -0.7247 | 0.3667 | -1.0915 |
| 0.6318 | 0.5233 | 500 | 2.6547 | 2.9545 | -155.4930 | -204.6371 | 0.6105 | 0.3552 | -0.8100 | 0.4251 | -1.2351 |
| 0.5978 | 0.6279 | 600 | 0.9606 | 1.4420 | -147.8560 | -199.5121 | 0.6015 | 0.3591 | -0.7336 | 0.4502 | -1.1838 |
| 0.6113 | 0.7326 | 700 | 1.1833 | 1.7188 | -150.6854 | -204.9195 | 0.5986 | 0.3651 | -0.7619 | 0.4760 | -1.2379 |
| 0.5885 | 0.8373 | 800 | 0.5613 | 1.0128 | -141.6925 | -192.4845 | 0.5974 | 0.3690 | -0.6720 | 0.4415 | -1.1136 |
| 0.595 | 0.9419 | 900 | 0.4326 | 0.9106 | -136.2882 | -189.5506 | 0.5958 | 0.3710 | -0.6180 | 0.4663 | -1.0842 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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