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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_qfUNL_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_qfUNL_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: 0.6685
- Sft Loss: 1.5897
- Rewards/chosen: -1.6017
- Rewards/rejected: -2.2330
- Rewards/accuracies: 0.6506
- Rewards/margins: 0.6314
- Logps/rejected: -2.2330
- Logps/chosen: -1.6017
- Logits/rejected: 0.2142
- Logits/chosen: 0.1178
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6889 | 0.2141 | 400 | 0.7003 | 1.4382 | -1.5229 | -1.6955 | 0.5579 | 0.1726 | -1.6955 | -1.5229 | 0.2817 | 0.1945 |
| 0.6916 | 0.4282 | 800 | 0.6822 | 1.5282 | -1.5414 | -1.8469 | 0.6076 | 0.3055 | -1.8469 | -1.5414 | 0.2875 | 0.2001 |
| 0.6757 | 0.6422 | 1200 | 0.6771 | 1.5574 | -1.5600 | -1.9539 | 0.6217 | 0.3939 | -1.9539 | -1.5600 | 0.2922 | 0.2043 |
| 0.6744 | 0.8563 | 1600 | 0.6739 | 1.5959 | -1.6093 | -2.0408 | 0.6335 | 0.4315 | -2.0408 | -1.6093 | 0.2827 | 0.1913 |
| 0.714 | 1.0704 | 2000 | 0.6719 | 1.5564 | -1.5625 | -2.0466 | 0.6269 | 0.4841 | -2.0466 | -1.5625 | 0.1990 | 0.1104 |
| 0.6715 | 1.2845 | 2400 | 0.6719 | 1.5799 | -1.5845 | -2.1083 | 0.6380 | 0.5238 | -2.1083 | -1.5845 | 0.2487 | 0.1536 |
| 0.6658 | 1.4986 | 2800 | 0.6707 | 1.6055 | -1.6197 | -2.1818 | 0.6454 | 0.5621 | -2.1818 | -1.6197 | 0.1108 | 0.0257 |
| 0.6709 | 1.7127 | 3200 | 0.6701 | 1.5845 | -1.5941 | -2.1721 | 0.6476 | 0.5780 | -2.1721 | -1.5941 | 0.1373 | 0.0502 |
| 0.659 | 1.9267 | 3600 | 0.6686 | 1.5568 | -1.5549 | -2.1383 | 0.6454 | 0.5835 | -2.1383 | -1.5549 | 0.1189 | 0.0332 |
| 0.6241 | 2.1408 | 4000 | 0.6689 | 1.5859 | -1.5837 | -2.1770 | 0.6454 | 0.5933 | -2.1770 | -1.5837 | 0.1840 | 0.0917 |
| 0.6443 | 2.3549 | 4400 | 0.6692 | 1.5919 | -1.6001 | -2.2168 | 0.6461 | 0.6166 | -2.2168 | -1.6001 | 0.0426 | -0.0398 |
| 0.6356 | 2.5690 | 4800 | 0.6686 | 1.5864 | -1.5964 | -2.2216 | 0.6484 | 0.6252 | -2.2216 | -1.5964 | 0.1106 | 0.0226 |
| 0.6448 | 2.7831 | 5200 | 0.6683 | 1.5882 | -1.5994 | -2.2308 | 0.6506 | 0.6314 | -2.2308 | -1.5994 | 0.0974 | 0.0105 |
| 0.6368 | 2.9972 | 5600 | 0.6685 | 1.5897 | -1.6017 | -2.2330 | 0.6506 | 0.6314 | -2.2330 | -1.6017 | 0.2142 | 0.1178 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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