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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_l21_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_l21_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: 0.6901
- Sft Loss: 2.1331
- Rewards/chosen: -2.1707
- Rewards/rejected: -3.2270
- Rewards/accuracies: 0.6914
- Rewards/margins: 1.0563
- Logps/rejected: -3.2270
- Logps/chosen: -2.1707
- Logits/rejected: 0.2151
- Logits/chosen: 0.1185
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7149 | 0.2141 | 400 | 0.7232 | 2.1337 | -3.3125 | -3.5682 | 0.5200 | 0.2557 | -3.5682 | -3.3125 | 0.5534 | 0.4407 |
| 0.7105 | 0.4282 | 800 | 0.7055 | 2.1066 | -2.2353 | -2.7243 | 0.6447 | 0.4890 | -2.7243 | -2.2353 | 0.3870 | 0.2857 |
| 0.7071 | 0.6422 | 1200 | 0.6988 | 2.0445 | -2.1363 | -2.7640 | 0.6691 | 0.6278 | -2.7640 | -2.1363 | 0.6763 | 0.5552 |
| 0.6909 | 0.8563 | 1600 | 0.6951 | 2.2316 | -2.3067 | -3.0785 | 0.6825 | 0.7718 | -3.0785 | -2.3067 | 0.0414 | -0.0345 |
| 0.6992 | 1.0704 | 2000 | 0.6927 | 2.0672 | -2.1384 | -2.9634 | 0.6766 | 0.8250 | -2.9634 | -2.1384 | 0.1253 | 0.0374 |
| 0.6894 | 1.2845 | 2400 | 0.6908 | 2.1132 | -2.1527 | -3.0987 | 0.6810 | 0.9460 | -3.0987 | -2.1527 | 0.3470 | 0.2424 |
| 0.6881 | 1.4986 | 2800 | 0.6908 | 2.1384 | -2.2307 | -3.1888 | 0.6862 | 0.9581 | -3.1888 | -2.2307 | 0.5238 | 0.4064 |
| 0.6998 | 1.7127 | 3200 | 0.6900 | 2.1093 | -2.1719 | -3.1258 | 0.6936 | 0.9539 | -3.1258 | -2.1719 | 0.2688 | 0.1694 |
| 0.6837 | 1.9267 | 3600 | 0.6898 | 2.1422 | -2.2075 | -3.2094 | 0.6966 | 1.0019 | -3.2094 | -2.2075 | 0.3036 | 0.1996 |
| 0.6446 | 2.1408 | 4000 | 0.6902 | 2.1614 | -2.1867 | -3.2140 | 0.6855 | 1.0273 | -3.2140 | -2.1867 | 0.2205 | 0.1222 |
| 0.6694 | 2.3549 | 4400 | 0.6887 | 2.1145 | -2.1590 | -3.1865 | 0.6921 | 1.0275 | -3.1865 | -2.1590 | 0.2474 | 0.1483 |
| 0.6722 | 2.5690 | 4800 | 0.6902 | 2.1289 | -2.1610 | -3.2026 | 0.6907 | 1.0415 | -3.2026 | -2.1610 | 0.2232 | 0.1258 |
| 0.6701 | 2.7831 | 5200 | 0.6904 | 2.1329 | -2.1699 | -3.2263 | 0.6929 | 1.0564 | -3.2263 | -2.1699 | 0.2407 | 0.1420 |
| 0.659 | 2.9972 | 5600 | 0.6901 | 2.1331 | -2.1707 | -3.2271 | 0.6914 | 1.0563 | -3.2271 | -2.1707 | 0.2151 | 0.1185 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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