File size: 4,746 Bytes
a5ae8e0 f64a019 a5ae8e0 f64a019 a5ae8e0 f64a019 a5ae8e0 b027249 a5ae8e0 b027249 a5ae8e0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
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_orpo_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_orpo_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: 0.5257
- Rewards/chosen: -5.2305
- Rewards/rejected: -6.3460
- Rewards/accuracies: 0.7285
- Rewards/margins: 1.1155
- Logps/rejected: -6.3460
- Logps/chosen: -5.2305
- Logits/rejected: 0.3311
- Logits/chosen: 0.2347
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7057 | 0.2141 | 400 | 0.7062 | -1.5154 | -1.6776 | 0.5571 | 0.1622 | -1.6776 | -1.5154 | 0.3357 | 0.2498 |
| 0.597 | 0.4282 | 800 | 0.5956 | -2.3371 | -2.7822 | 0.6669 | 0.4451 | -2.7822 | -2.3371 | 0.4528 | 0.3584 |
| 0.5883 | 0.6422 | 1200 | 0.5486 | -3.5511 | -4.2123 | 0.7211 | 0.6612 | -4.2123 | -3.5511 | 0.3923 | 0.2876 |
| 0.4794 | 0.8563 | 1600 | 0.5320 | -3.5255 | -4.2178 | 0.7277 | 0.6924 | -4.2178 | -3.5255 | 0.3881 | 0.2849 |
| 0.5765 | 1.0704 | 2000 | 0.5305 | -3.6701 | -4.4352 | 0.7240 | 0.7651 | -4.4352 | -3.6701 | 0.3104 | 0.1978 |
| 0.5449 | 1.2845 | 2400 | 0.5198 | -4.3149 | -5.2348 | 0.7352 | 0.9199 | -5.2348 | -4.3149 | 0.2247 | 0.1184 |
| 0.518 | 1.4986 | 2800 | 0.5189 | -4.2439 | -5.1423 | 0.7352 | 0.8983 | -5.1423 | -4.2439 | 0.3318 | 0.2186 |
| 0.5602 | 1.7127 | 3200 | 0.5174 | -4.3315 | -5.2509 | 0.7381 | 0.9194 | -5.2509 | -4.3315 | 0.3472 | 0.2362 |
| 0.5482 | 1.9267 | 3600 | 0.5152 | -4.3680 | -5.3320 | 0.7329 | 0.9640 | -5.3320 | -4.3680 | 0.3330 | 0.2233 |
| 0.4259 | 2.1408 | 4000 | 0.5296 | -5.1372 | -6.2156 | 0.7270 | 1.0783 | -6.2156 | -5.1372 | 0.3103 | 0.2143 |
| 0.4141 | 2.3549 | 4400 | 0.5245 | -5.3001 | -6.3996 | 0.7277 | 1.0995 | -6.3996 | -5.3001 | 0.3776 | 0.2775 |
| 0.4481 | 2.5690 | 4800 | 0.5253 | -5.2343 | -6.3529 | 0.7307 | 1.1185 | -6.3529 | -5.2343 | 0.4139 | 0.3107 |
| 0.3925 | 2.7831 | 5200 | 0.5251 | -5.2099 | -6.3202 | 0.7285 | 1.1103 | -6.3202 | -5.2099 | 0.3386 | 0.2411 |
| 0.4044 | 2.9972 | 5600 | 0.5257 | -5.2305 | -6.3460 | 0.7285 | 1.1155 | -6.3460 | -5.2305 | 0.3311 | 0.2347 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
|