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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
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
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: 0.6612
- Rewards/chosen: -4.9613
- Rewards/rejected: -8.3580
- Rewards/accuracies: 0.6766
- Rewards/margins: 3.3967
- Logps/rejected: -8.3580
- Logps/chosen: -4.9613
- Logits/rejected: 1.3373
- Logits/chosen: 0.9296
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6893 | 0.2141 | 400 | 0.6976 | -5.6399 | -5.6514 | 0.5134 | 0.0115 | -5.6514 | -5.6399 | 0.6073 | 0.4970 |
| 0.6905 | 0.4282 | 800 | 0.6888 | -9.5942 | -10.2217 | 0.5772 | 0.6275 | -10.2217 | -9.5942 | 0.9367 | 0.7851 |
| 0.6827 | 0.6422 | 1200 | 0.6809 | -3.7037 | -4.6831 | 0.6417 | 0.9794 | -4.6831 | -3.7037 | 0.4628 | 0.3100 |
| 0.665 | 0.8563 | 1600 | 0.6737 | -4.1597 | -6.3017 | 0.6588 | 2.1420 | -6.3017 | -4.1597 | 0.9087 | 0.6452 |
| 0.674 | 1.0704 | 2000 | 0.6702 | -4.7093 | -7.4594 | 0.6677 | 2.7501 | -7.4594 | -4.7093 | 1.0243 | 0.7072 |
| 0.6648 | 1.2845 | 2400 | 0.6651 | -4.2327 | -7.0267 | 0.6654 | 2.7940 | -7.0267 | -4.2327 | 0.9760 | 0.6519 |
| 0.6665 | 1.4986 | 2800 | 0.6654 | -4.6367 | -7.6607 | 0.6706 | 3.0240 | -7.6607 | -4.6367 | 1.0821 | 0.7239 |
| 0.6746 | 1.7127 | 3200 | 0.6641 | -5.1015 | -8.2207 | 0.6803 | 3.1192 | -8.2207 | -5.1015 | 1.0711 | 0.6993 |
| 0.6634 | 1.9267 | 3600 | 0.6629 | -4.7411 | -7.8576 | 0.6855 | 3.1165 | -7.8576 | -4.7411 | 1.0738 | 0.7086 |
| 0.6224 | 2.1408 | 4000 | 0.6607 | -4.6523 | -7.8867 | 0.6818 | 3.2344 | -7.8867 | -4.6523 | 1.1108 | 0.7335 |
| 0.6604 | 2.3549 | 4400 | 0.6618 | -4.7746 | -8.0447 | 0.6780 | 3.2700 | -8.0447 | -4.7746 | 1.2654 | 0.8695 |
| 0.6512 | 2.5690 | 4800 | 0.6615 | -4.9147 | -8.2777 | 0.6773 | 3.3630 | -8.2777 | -4.9147 | 1.2819 | 0.8805 |
| 0.6594 | 2.7831 | 5200 | 0.6611 | -4.9802 | -8.3859 | 0.6795 | 3.4057 | -8.3859 | -4.9802 | 1.2711 | 0.8676 |
| 0.6402 | 2.9972 | 5600 | 0.6612 | -4.9613 | -8.3580 | 0.6766 | 3.3967 | -8.3580 | -4.9613 | 1.3373 | 0.9296 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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