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---
library_name: transformers
license: other
base_model: trl-lib/qwen1.5-0.5b-sft
tags:
- alignment-handbook
- trl
- simpo
- generated_from_trainer
- trl
- simpo
- generated_from_trainer
datasets:
- yakazimir/ultrafeedback_binarized
model-index:
- name: qwen_cCPO_entropy_0_01
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. -->
# qwen_cCPO_entropy_0_01
This model is a fine-tuned version of [trl-lib/qwen1.5-0.5b-sft](https://huggingface.co/trl-lib/qwen1.5-0.5b-sft) on the yakazimir/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4896
- Sft Loss: 1.6913
- Rewards/chosen: -1.6159
- Rewards/rejected: -2.1942
- Rewards/accuracies: 0.6714
- Rewards/margins: 0.5783
- Logps/rejected: -2.1942
- Logps/chosen: -1.6159
- Logits/rejected: 0.2372
- Logits/chosen: 0.1346
## 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: 1e-06
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_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: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Sft Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5602 | 0.2141 | 400 | 0.5593 | 1.3702 | -1.3432 | -1.4801 | 0.5579 | 0.1369 | -1.4801 | -1.3432 | 0.3397 | 0.2525 |
| 0.5448 | 0.4282 | 800 | 0.5318 | 1.4044 | -1.3785 | -1.6209 | 0.5883 | 0.2424 | -1.6209 | -1.3785 | 0.3618 | 0.2727 |
| 0.5415 | 0.6422 | 1200 | 0.5156 | 1.4648 | -1.4398 | -1.7890 | 0.6187 | 0.3493 | -1.7890 | -1.4398 | 0.3220 | 0.2312 |
| 0.4953 | 0.8563 | 1600 | 0.5101 | 1.4980 | -1.4449 | -1.7958 | 0.6261 | 0.3509 | -1.7958 | -1.4449 | 0.3743 | 0.2752 |
| 0.5743 | 1.0704 | 2000 | 0.5047 | 1.4884 | -1.4330 | -1.8072 | 0.6306 | 0.3742 | -1.8072 | -1.4330 | 0.3107 | 0.2131 |
| 0.4824 | 1.2845 | 2400 | 0.4963 | 1.6007 | -1.5341 | -2.0179 | 0.6536 | 0.4838 | -2.0179 | -1.5341 | 0.3099 | 0.2106 |
| 0.5266 | 1.4986 | 2800 | 0.4947 | 1.6155 | -1.5391 | -2.0193 | 0.6573 | 0.4801 | -2.0193 | -1.5391 | 0.2939 | 0.1953 |
| 0.5053 | 1.7127 | 3200 | 0.4936 | 1.5759 | -1.5037 | -1.9595 | 0.6484 | 0.4558 | -1.9595 | -1.5037 | 0.3131 | 0.2133 |
| 0.4712 | 1.9267 | 3600 | 0.4894 | 1.6467 | -1.5640 | -2.0770 | 0.6662 | 0.5129 | -2.0770 | -1.5640 | 0.3113 | 0.2089 |
| 0.4297 | 2.1408 | 4000 | 0.4894 | 1.6624 | -1.5827 | -2.1264 | 0.6699 | 0.5437 | -2.1264 | -1.5827 | 0.2311 | 0.1311 |
| 0.4418 | 2.3549 | 4400 | 0.4909 | 1.7121 | -1.6395 | -2.2277 | 0.6736 | 0.5882 | -2.2277 | -1.6395 | 0.2582 | 0.1535 |
| 0.4422 | 2.5690 | 4800 | 0.4894 | 1.6890 | -1.6151 | -2.1880 | 0.6699 | 0.5729 | -2.1880 | -1.6151 | 0.2371 | 0.1340 |
| 0.4463 | 2.7831 | 5200 | 0.4895 | 1.6851 | -1.6106 | -2.1856 | 0.6706 | 0.5751 | -2.1856 | -1.6106 | 0.2327 | 0.1306 |
| 0.4311 | 2.9972 | 5600 | 0.4896 | 1.6913 | -1.6159 | -2.1942 | 0.6714 | 0.5783 | -2.1942 | -1.6159 | 0.2372 | 0.1346 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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