metadata
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_cpo_entropy_0_3
results: []
qwen_cpo_entropy_0_3
This model is a fine-tuned version of trl-lib/qwen1.5-0.5b-sft on the yakazimir/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 1.0416
- Sft Loss: 1.4031
- Rewards/chosen: -1.3990
- Rewards/rejected: -1.8440
- Rewards/accuracies: 0.6157
- Rewards/margins: 0.4450
- Logps/rejected: -1.8440
- Logps/chosen: -1.3990
- Logits/rejected: 0.2187
- Logits/chosen: 0.1269
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.09 | 0.2141 | 400 | 1.1010 | 1.3681 | -1.3477 | -1.4855 | 0.5586 | 0.1378 | -1.4855 | -1.3477 | 0.3207 | 0.2350 |
| 1.0764 | 0.4282 | 800 | 1.0739 | 1.3759 | -1.3603 | -1.5873 | 0.5823 | 0.2270 | -1.5873 | -1.3603 | 0.3806 | 0.2884 |
| 1.077 | 0.6422 | 1200 | 1.0591 | 1.3822 | -1.3685 | -1.6704 | 0.5935 | 0.3019 | -1.6704 | -1.3685 | 0.3589 | 0.2649 |
| 1.0489 | 0.8563 | 1600 | 1.0555 | 1.3767 | -1.3518 | -1.6477 | 0.5905 | 0.2959 | -1.6477 | -1.3518 | 0.4297 | 0.3293 |
| 1.1366 | 1.0704 | 2000 | 1.0496 | 1.3798 | -1.3555 | -1.7040 | 0.5987 | 0.3484 | -1.7040 | -1.3555 | 0.3416 | 0.2453 |
| 1.0133 | 1.2845 | 2400 | 1.0461 | 1.3864 | -1.3639 | -1.7321 | 0.6053 | 0.3682 | -1.7321 | -1.3639 | 0.3701 | 0.2708 |
| 1.1144 | 1.4986 | 2800 | 1.0443 | 1.3887 | -1.3652 | -1.7447 | 0.6105 | 0.3794 | -1.7447 | -1.3652 | 0.2150 | 0.1278 |
| 1.0196 | 1.7127 | 3200 | 1.0449 | 1.3841 | -1.3615 | -1.7338 | 0.6142 | 0.3723 | -1.7338 | -1.3615 | 0.1872 | 0.1007 |
| 1.0023 | 1.9267 | 3600 | 1.0405 | 1.3927 | -1.3767 | -1.7830 | 0.6120 | 0.4063 | -1.7830 | -1.3767 | 0.2211 | 0.1322 |
| 0.9654 | 2.1408 | 4000 | 1.0418 | 1.3967 | -1.3910 | -1.8183 | 0.6180 | 0.4273 | -1.8183 | -1.3910 | 0.2405 | 0.1482 |
| 0.9676 | 2.3549 | 4400 | 1.0418 | 1.4054 | -1.4061 | -1.8540 | 0.6231 | 0.4479 | -1.8540 | -1.4061 | 0.2064 | 0.1158 |
| 0.9789 | 2.5690 | 4800 | 1.0420 | 1.4009 | -1.3974 | -1.8380 | 0.6142 | 0.4406 | -1.8380 | -1.3974 | 0.1887 | 0.0996 |
| 1.0003 | 2.7831 | 5200 | 1.0413 | 1.4027 | -1.3986 | -1.8438 | 0.6187 | 0.4452 | -1.8438 | -1.3986 | 0.2046 | 0.1137 |
| 0.9909 | 2.9972 | 5600 | 1.0416 | 1.4031 | -1.3990 | -1.8440 | 0.6157 | 0.4450 | -1.8440 | -1.3990 | 0.2187 | 0.1269 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1