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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-9e-07-0.86-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-9e-07-0.86-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: 1.2207
- Rewards/chosen: 0.7526
- Rewards/rejected: -1.3224
- Rewards/accuracies: 0.3294
- Rewards/margins: 2.0750
- Logps/rejected: -82.6661
- Logps/chosen: -73.6161
- Logits/rejected: -2.6026
- Logits/chosen: -2.6190
## 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: 9e-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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.9734 | 0.3484 | 100 | 0.9203 | 2.0652 | 1.3351 | 0.3294 | 0.7302 | -79.5760 | -72.0898 | -2.5695 | -2.5853 |
| 0.9883 | 0.6969 | 200 | 1.0967 | 2.4271 | 1.1885 | 0.3373 | 1.2386 | -79.7464 | -71.6691 | -2.5708 | -2.5875 |
| 0.4215 | 1.0453 | 300 | 1.1234 | 3.0876 | 1.7905 | 0.3313 | 1.2970 | -79.0463 | -70.9010 | -2.6403 | -2.6560 |
| 0.393 | 1.3937 | 400 | 1.2234 | -0.1343 | -1.8934 | 0.3234 | 1.7591 | -83.3299 | -74.6474 | -2.6093 | -2.6250 |
| 0.3986 | 1.7422 | 500 | 1.2247 | 0.1937 | -1.8484 | 0.3214 | 2.0420 | -83.2776 | -74.2660 | -2.5909 | -2.6070 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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