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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_cfUNL_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_cfUNL_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: 0.0501
- Sft Loss: 3.9427
- Rewards/chosen: -4.3435
- Rewards/rejected: -5.1114
- Rewards/accuracies: 0.6810
- Rewards/margins: 0.7679
- Logps/rejected: -5.1114
- Logps/chosen: -4.3435
- Logits/rejected: -0.0604
- Logits/chosen: -0.1374
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0548 | 0.2141 | 400 | 0.0564 | 4.2256 | -4.8288 | -5.0421 | 0.5378 | 0.2133 | -5.0421 | -4.8288 | 0.4440 | 0.3255 |
| 0.0531 | 0.4282 | 800 | 0.0526 | 4.0511 | -4.5660 | -4.9392 | 0.6157 | 0.3732 | -4.9392 | -4.5660 | 0.2541 | 0.1294 |
| 0.0534 | 0.6422 | 1200 | 0.0519 | 4.1663 | -4.5650 | -5.0390 | 0.6387 | 0.4740 | -5.0390 | -4.5650 | 0.2502 | 0.1373 |
| 0.0511 | 0.8563 | 1600 | 0.0513 | 3.9593 | -4.4389 | -4.9222 | 0.6358 | 0.4833 | -4.9222 | -4.4389 | -0.0640 | -0.1524 |
| 0.0533 | 1.0704 | 2000 | 0.0509 | 3.9533 | -4.4316 | -4.9577 | 0.6484 | 0.5261 | -4.9577 | -4.4316 | -0.0257 | -0.1111 |
| 0.0527 | 1.2845 | 2400 | 0.0508 | 4.2818 | -4.7129 | -5.3738 | 0.6610 | 0.6609 | -5.3738 | -4.7129 | -0.0551 | -0.1386 |
| 0.0513 | 1.4986 | 2800 | 0.0506 | 4.1502 | -4.4933 | -5.1357 | 0.6818 | 0.6424 | -5.1357 | -4.4933 | -0.1729 | -0.2577 |
| 0.0527 | 1.7127 | 3200 | 0.0505 | 4.1082 | -4.4722 | -5.1175 | 0.6743 | 0.6453 | -5.1175 | -4.4722 | -0.0614 | -0.1521 |
| 0.0538 | 1.9267 | 3600 | 0.0502 | 4.0026 | -4.3928 | -5.1056 | 0.6706 | 0.7129 | -5.1056 | -4.3928 | -0.1185 | -0.1939 |
| 0.0495 | 2.1408 | 4000 | 0.0502 | 4.0304 | -4.4251 | -5.1723 | 0.6825 | 0.7472 | -5.1723 | -4.4251 | -0.0488 | -0.1284 |
| 0.0522 | 2.3549 | 4400 | 0.0501 | 3.9711 | -4.3751 | -5.1111 | 0.6751 | 0.7360 | -5.1111 | -4.3751 | -0.1449 | -0.2170 |
| 0.0517 | 2.5690 | 4800 | 0.0501 | 4.0093 | -4.3976 | -5.1429 | 0.6832 | 0.7452 | -5.1429 | -4.3976 | -0.0508 | -0.1310 |
| 0.0496 | 2.7831 | 5200 | 0.0501 | 3.9605 | -4.3494 | -5.1084 | 0.6788 | 0.7590 | -5.1084 | -4.3494 | -0.0700 | -0.1475 |
| 0.0497 | 2.9972 | 5600 | 0.0501 | 3.9427 | -4.3435 | -5.1114 | 0.6810 | 0.7679 | -5.1114 | -4.3435 | -0.0604 | -0.1374 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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