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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_fUNL_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_fUNL_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: 0.0504
- Sft Loss: 4.0281
- Rewards/chosen: -4.4231
- Rewards/rejected: -5.1418
- Rewards/accuracies: 0.6862
- Rewards/margins: 0.7187
- Logps/rejected: -5.1418
- Logps/chosen: -4.4231
- Logits/rejected: -0.2955
- Logits/chosen: -0.3687
## 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 | 0.0557 | 4.8295 | -5.3467 | -5.4723 | 0.5326 | 0.1256 | -5.4723 | -5.3467 | 0.1095 | -0.0277 |
| 0.0537 | 0.4282 | 800 | 0.0529 | 4.1330 | -4.6614 | -4.9903 | 0.6024 | 0.3289 | -4.9903 | -4.6614 | 0.2188 | 0.0763 |
| 0.0545 | 0.6422 | 1200 | 0.0523 | 4.2856 | -4.6580 | -5.0486 | 0.6350 | 0.3906 | -5.0486 | -4.6580 | 0.0914 | -0.0257 |
| 0.0518 | 0.8563 | 1600 | 0.0519 | 4.0636 | -4.5007 | -4.9176 | 0.6313 | 0.4169 | -4.9176 | -4.5007 | 0.0782 | -0.0290 |
| 0.0537 | 1.0704 | 2000 | 0.0517 | 3.9662 | -4.4270 | -4.8924 | 0.6469 | 0.4654 | -4.8924 | -4.4270 | -0.1550 | -0.2400 |
| 0.0533 | 1.2845 | 2400 | 0.0514 | 4.4069 | -4.8229 | -5.4257 | 0.6632 | 0.6028 | -5.4257 | -4.8229 | -0.1556 | -0.2460 |
| 0.0522 | 1.4986 | 2800 | 0.0511 | 4.2244 | -4.5446 | -5.1374 | 0.6803 | 0.5928 | -5.1374 | -4.5446 | -0.2984 | -0.3849 |
| 0.053 | 1.7127 | 3200 | 0.0508 | 4.1193 | -4.4960 | -5.1073 | 0.6691 | 0.6113 | -5.1073 | -4.4960 | -0.2032 | -0.2947 |
| 0.0538 | 1.9267 | 3600 | 0.0505 | 4.0434 | -4.4193 | -5.0638 | 0.6847 | 0.6445 | -5.0638 | -4.4193 | -0.2476 | -0.3292 |
| 0.0504 | 2.1408 | 4000 | 0.0505 | 4.0585 | -4.4646 | -5.1658 | 0.6840 | 0.7011 | -5.1658 | -4.4646 | -0.2103 | -0.2919 |
| 0.053 | 2.3549 | 4400 | 0.0505 | 4.0905 | -4.4767 | -5.1722 | 0.6840 | 0.6956 | -5.1722 | -4.4767 | -0.2850 | -0.3632 |
| 0.0525 | 2.5690 | 4800 | 0.0504 | 4.0700 | -4.4483 | -5.1426 | 0.6832 | 0.6943 | -5.1426 | -4.4483 | -0.1890 | -0.2741 |
| 0.0509 | 2.7831 | 5200 | 0.0504 | 4.0135 | -4.3932 | -5.0993 | 0.6855 | 0.7061 | -5.0993 | -4.3932 | -0.1516 | -0.2376 |
| 0.0504 | 2.9972 | 5600 | 0.0504 | 4.0281 | -4.4231 | -5.1418 | 0.6862 | 0.7187 | -5.1418 | -4.4231 | -0.2955 | -0.3687 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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