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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_uncCPO_entropy
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_uncCPO_entropy
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: 0.0000
- Rewards/chosen: -46.3149
- Rewards/rejected: -47.3422
- Rewards/accuracies: 0.5616
- Rewards/margins: 1.0272
- Logps/rejected: -47.3422
- Logps/chosen: -46.3149
- Logits/rejected: 7.3215
- Logits/chosen: 7.6457
## 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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0 | 0.2141 | 400 | 0.0001 | -31.9619 | -33.7423 | 0.5660 | 1.7804 | -33.7423 | -31.9619 | 4.6072 | 4.6195 |
| 0.0 | 0.4282 | 800 | 0.0000 | -39.5193 | -40.9236 | 0.5593 | 1.4042 | -40.9236 | -39.5193 | 6.2657 | 6.4289 |
| 0.0008 | 0.6422 | 1200 | 0.0000 | -39.2251 | -40.6025 | 0.5542 | 1.3774 | -40.6025 | -39.2251 | 6.1312 | 6.2908 |
| 0.0 | 0.8563 | 1600 | 0.0000 | -41.1464 | -42.5420 | 0.5638 | 1.3956 | -42.5420 | -41.1464 | 6.3830 | 6.5549 |
| 0.0 | 1.0704 | 2000 | 0.0000 | -43.4369 | -44.6769 | 0.5734 | 1.2400 | -44.6769 | -43.4369 | 6.8661 | 7.0992 |
| 0.0 | 1.2845 | 2400 | 0.0000 | -43.9619 | -45.1746 | 0.5697 | 1.2127 | -45.1746 | -43.9619 | 6.9058 | 7.1560 |
| 0.0 | 1.4986 | 2800 | 0.0000 | -44.1897 | -45.3701 | 0.5645 | 1.1803 | -45.3701 | -44.1897 | 6.8977 | 7.1567 |
| 0.0 | 1.7127 | 3200 | 0.0000 | -44.9141 | -46.0263 | 0.5660 | 1.1122 | -46.0263 | -44.9141 | 7.0833 | 7.3687 |
| 0.0 | 1.9267 | 3600 | 0.0000 | -45.5997 | -46.6466 | 0.5645 | 1.0470 | -46.6466 | -45.5997 | 7.1427 | 7.4593 |
| 0.0 | 2.1408 | 4000 | 0.0000 | -45.8198 | -46.8818 | 0.5601 | 1.0620 | -46.8818 | -45.8198 | 7.2832 | 7.5923 |
| 0.0 | 2.3549 | 4400 | 0.0000 | -45.8900 | -46.9389 | 0.5653 | 1.0489 | -46.9389 | -45.8900 | 7.2655 | 7.5788 |
| 0.0 | 2.5690 | 4800 | 0.0000 | -45.9866 | -47.0244 | 0.5623 | 1.0378 | -47.0244 | -45.9866 | 7.2594 | 7.5758 |
| 0.0 | 2.7831 | 5200 | 0.0000 | -45.8574 | -46.9081 | 0.5623 | 1.0507 | -46.9081 | -45.8574 | 7.2536 | 7.5634 |
| 0.0 | 2.9972 | 5600 | 0.0000 | -46.3149 | -47.3422 | 0.5616 | 1.0272 | -47.3422 | -46.3149 | 7.3215 | 7.6457 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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