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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
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
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: 0.0000
- Rewards/chosen: -42.7794
- Rewards/rejected: -43.9149
- Rewards/accuracies: 0.5668
- Rewards/margins: 1.1356
- Logps/rejected: -43.9149
- Logps/chosen: -42.7794
- Logits/rejected: 7.2567
- Logits/chosen: 7.5393
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0 | 0.2141 | 400 | 0.0001 | -29.4740 | -31.2238 | 0.5690 | 1.7498 | -31.2238 | -29.4740 | 4.5258 | 4.5083 |
| 0.0 | 0.4282 | 800 | 0.0000 | -37.0465 | -38.5277 | 0.5579 | 1.4811 | -38.5277 | -37.0465 | 6.2307 | 6.3643 |
| 0.001 | 0.6422 | 1200 | 0.0000 | -38.7942 | -40.1267 | 0.5668 | 1.3324 | -40.1267 | -38.7942 | 6.5149 | 6.7000 |
| 0.0 | 0.8563 | 1600 | 0.0000 | -38.5913 | -40.0107 | 0.5668 | 1.4194 | -40.0107 | -38.5913 | 6.5708 | 6.7471 |
| 0.0 | 1.0704 | 2000 | 0.0000 | -40.7799 | -42.0174 | 0.5675 | 1.2374 | -42.0174 | -40.7799 | 7.0075 | 7.2451 |
| 0.0 | 1.2845 | 2400 | 0.0000 | -40.9809 | -42.2090 | 0.5645 | 1.2280 | -42.2090 | -40.9809 | 6.9425 | 7.1883 |
| 0.0 | 1.4986 | 2800 | 0.0000 | -41.7185 | -42.9016 | 0.5631 | 1.1831 | -42.9016 | -41.7185 | 7.2071 | 7.4629 |
| 0.0 | 1.7127 | 3200 | 0.0000 | -41.7373 | -42.9487 | 0.5675 | 1.2115 | -42.9487 | -41.7373 | 7.0907 | 7.3464 |
| 0.0 | 1.9267 | 3600 | 0.0000 | -42.3165 | -43.4863 | 0.5668 | 1.1698 | -43.4863 | -42.3165 | 7.2080 | 7.4815 |
| 0.0 | 2.1408 | 4000 | 0.0000 | -43.0385 | -44.1473 | 0.5697 | 1.1088 | -44.1473 | -43.0385 | 7.2552 | 7.5548 |
| 0.0 | 2.3549 | 4400 | 0.0000 | -42.9448 | -44.0525 | 0.5705 | 1.1077 | -44.0525 | -42.9448 | 7.2918 | 7.5836 |
| 0.0 | 2.5690 | 4800 | 0.0000 | -43.0768 | -44.1767 | 0.5675 | 1.0999 | -44.1767 | -43.0768 | 7.3794 | 7.6690 |
| 0.0 | 2.7831 | 5200 | 0.0000 | -43.1227 | -44.2291 | 0.5690 | 1.1064 | -44.2291 | -43.1227 | 7.2960 | 7.5933 |
| 0.0 | 2.9972 | 5600 | 0.0000 | -42.7794 | -43.9149 | 0.5668 | 1.1356 | -43.9149 | -42.7794 | 7.2567 | 7.5393 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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