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_unl_entropy_0_0
results: []
qwen_unl_entropy_0_0
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: 1.6479
- Rewards/chosen: -1.3032
- Rewards/rejected: -1.4993
- Rewards/accuracies: 0.5712
- Rewards/margins: 0.1961
- Logps/rejected: -1.4993
- Logps/chosen: -1.3032
- 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