---
library_name: transformers
license: other
base_model: trl-lib/qwen1.5-0.5b-sft
tags:
- trl
- simpo
- generated_from_trainer
model-index:
- name: qwen_unl_entropy_0_0
  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_unl_entropy_0_0

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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6479
- Rewards/chosen: -1.3031
- Rewards/rejected: -1.4993
- Rewards/accuracies: 0.5712
- Rewards/margins: 0.1961
- Logps/rejected: -1.4993
- Logps/chosen: -1.3031
- Logits/rejected: 0.1464
- Logits/chosen: 0.0748

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 1.6555        | 0.2141 | 400  | 1.6941          | -1.3383        | -1.4640          | 0.5556             | 0.1257          | -1.4640        | -1.3383      | 0.4030          | 0.3137        |
| 1.6693        | 0.4282 | 800  | 1.6719          | -1.3149        | -1.4532          | 0.5579             | 0.1383          | -1.4532        | -1.3149      | 0.3441          | 0.2642        |
| 1.6204        | 0.6422 | 1200 | 1.6640          | -1.3085        | -1.4525          | 0.5556             | 0.1440          | -1.4525        | -1.3085      | 0.3559          | 0.2746        |
| 1.6569        | 0.8563 | 1600 | 1.6598          | -1.3094        | -1.4585          | 0.5593             | 0.1491          | -1.4585        | -1.3094      | 0.2618          | 0.1878        |
| 1.7111        | 1.0704 | 2000 | 1.6548          | -1.3002        | -1.4570          | 0.5653             | 0.1568          | -1.4570        | -1.3002      | 0.2290          | 0.1561        |
| 1.6123        | 1.2845 | 2400 | 1.6522          | -1.3029        | -1.4741          | 0.5675             | 0.1711          | -1.4741        | -1.3029      | 0.2729          | 0.1950        |
| 1.6687        | 1.4986 | 2800 | 1.6488          | -1.3000        | -1.4737          | 0.5697             | 0.1738          | -1.4737        | -1.3000      | 0.1754          | 0.1051        |
| 1.6012        | 1.7127 | 3200 | 1.6494          | -1.3010        | -1.4718          | 0.5675             | 0.1708          | -1.4718        | -1.3010      | 0.1848          | 0.1133        |
| 1.5646        | 1.9267 | 3600 | 1.6479          | -1.2987        | -1.4776          | 0.5682             | 0.1789          | -1.4776        | -1.2987      | 0.1466          | 0.0770        |
| 1.5351        | 2.1408 | 4000 | 1.6470          | -1.3020        | -1.4960          | 0.5697             | 0.1940          | -1.4960        | -1.3020      | 0.1418          | 0.0714        |
| 1.5309        | 2.3549 | 4400 | 1.6467          | -1.3051        | -1.5042          | 0.5727             | 0.1991          | -1.5042        | -1.3051      | 0.1132          | 0.0439        |
| 1.5444        | 2.5690 | 4800 | 1.6473          | -1.3034        | -1.5014          | 0.5720             | 0.1979          | -1.5014        | -1.3034      | 0.1403          | 0.0690        |
| 1.5671        | 2.7831 | 5200 | 1.6474          | -1.3030        | -1.4996          | 0.5705             | 0.1966          | -1.4996        | -1.3030      | 0.2002          | 0.1244        |
| 1.5485        | 2.9972 | 5600 | 1.6479          | -1.3031        | -1.4993          | 0.5712             | 0.1961          | -1.4993        | -1.3031      | 0.1464          | 0.0748        |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1