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---
library_name: transformers
tags:
- trl
- dpo
- alignment-handbook
- generated_from_trainer
model-index:
- name: OpenELM-1_1B-DPO-full-max-reward-most-similar
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. -->
# OpenELM-1_1B-DPO-full-max-reward-most-similar
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6465
- Rewards/chosen: -17.75
- Rewards/rejected: -19.75
- Rewards/accuracies: 0.6055
- Rewards/margins: 2.0469
- Logps/rejected: -2272.0
- Logps/chosen: -2096.0
- Logits/rejected: 2.0312
- Logits/chosen: 0.2393
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5786 | 0.1047 | 100 | 0.6689 | -1.8203 | -2.0625 | 0.6094 | 0.2373 | -494.0 | -500.0 | -9.25 | -9.75 |
| 0.5359 | 0.2094 | 200 | 0.7366 | -3.3281 | -3.8125 | 0.5898 | 0.4824 | -672.0 | -652.0 | -1.7812 | -2.8906 |
| 0.5163 | 0.3141 | 300 | 0.6974 | -4.25 | -4.8438 | 0.6426 | 0.6016 | -776.0 | -744.0 | -5.4688 | -6.75 |
| 0.5127 | 0.4188 | 400 | 0.7937 | -5.375 | -6.0625 | 0.6016 | 0.6797 | -896.0 | -856.0 | -7.9375 | -9.125 |
| 0.5047 | 0.5236 | 500 | 0.7909 | -4.5938 | -5.2188 | 0.5703 | 0.6523 | -812.0 | -776.0 | -3.7188 | -5.5938 |
| 0.5057 | 0.6283 | 600 | 0.8288 | -5.375 | -6.125 | 0.5918 | 0.7539 | -904.0 | -856.0 | -4.5 | -6.4062 |
| 0.48 | 0.7330 | 700 | 0.7987 | -5.5312 | -6.4062 | 0.6289 | 0.8633 | -928.0 | -872.0 | -3.8438 | -5.6562 |
| 0.4751 | 0.8377 | 800 | 0.8430 | -7.0625 | -7.7812 | 0.5586 | 0.7070 | -1064.0 | -1024.0 | -4.3125 | -6.125 |
| 0.4408 | 0.9424 | 900 | 0.8971 | -8.3125 | -9.1875 | 0.5996 | 0.9023 | -1208.0 | -1152.0 | -6.3438 | -8.1875 |
| 0.1609 | 1.0471 | 1000 | 0.9796 | -8.1875 | -9.1875 | 0.5996 | 1.0156 | -1208.0 | -1136.0 | -1.7734 | -3.7656 |
| 0.1551 | 1.1518 | 1100 | 1.2334 | -13.8125 | -15.0625 | 0.5938 | 1.2422 | -1792.0 | -1704.0 | -0.2617 | -2.0312 |
| 0.1584 | 1.2565 | 1200 | 1.0642 | -10.375 | -11.5625 | 0.5918 | 1.1641 | -1440.0 | -1360.0 | -2.1875 | -3.9844 |
| 0.1618 | 1.3613 | 1300 | 0.9750 | -9.1875 | -10.3125 | 0.6211 | 1.1484 | -1320.0 | -1240.0 | -1.25 | -3.0781 |
| 0.1667 | 1.4660 | 1400 | 1.0401 | -9.75 | -11.125 | 0.6191 | 1.3125 | -1400.0 | -1296.0 | -1.1094 | -3.1875 |
| 0.1714 | 1.5707 | 1500 | 1.0380 | -10.6875 | -12.0625 | 0.6230 | 1.3438 | -1496.0 | -1392.0 | -0.2578 | -2.1719 |
| 0.1406 | 1.6754 | 1600 | 1.0427 | -11.25 | -12.625 | 0.6211 | 1.375 | -1552.0 | -1440.0 | -0.0874 | -2.0469 |
| 0.1195 | 1.7801 | 1700 | 1.1374 | -12.25 | -13.625 | 0.6133 | 1.3906 | -1648.0 | -1544.0 | -0.4316 | -2.1875 |
| 0.1291 | 1.8848 | 1800 | 1.0742 | -11.6875 | -13.0625 | 0.5938 | 1.3438 | -1592.0 | -1488.0 | 0.0305 | -1.7344 |
| 0.1236 | 1.9895 | 1900 | 1.1539 | -13.0 | -14.375 | 0.5840 | 1.3984 | -1728.0 | -1616.0 | 0.7383 | -0.9727 |
| 0.0264 | 2.0942 | 2000 | 1.5533 | -16.5 | -18.25 | 0.5840 | 1.75 | -2112.0 | -1968.0 | 1.1562 | -0.625 |
| 0.0222 | 2.1990 | 2100 | 1.6053 | -17.375 | -19.25 | 0.5957 | 1.8906 | -2224.0 | -2064.0 | 2.0781 | 0.3105 |
| 0.0266 | 2.3037 | 2200 | 1.5843 | -17.125 | -19.0 | 0.6055 | 1.8672 | -2192.0 | -2032.0 | 1.9297 | 0.0918 |
| 0.0247 | 2.4084 | 2300 | 1.6309 | -17.875 | -19.875 | 0.6094 | 2.0 | -2288.0 | -2112.0 | 2.1719 | 0.3652 |
| 0.0381 | 2.5131 | 2400 | 1.6237 | -17.75 | -19.625 | 0.6055 | 1.9219 | -2256.0 | -2096.0 | 2.0 | 0.2354 |
| 0.0307 | 2.6178 | 2500 | 1.6102 | -17.375 | -19.375 | 0.6055 | 2.0156 | -2224.0 | -2064.0 | 1.9141 | 0.1069 |
| 0.0259 | 2.7225 | 2600 | 1.6399 | -17.75 | -19.75 | 0.6035 | 2.0469 | -2272.0 | -2096.0 | 2.0469 | 0.2773 |
| 0.0279 | 2.8272 | 2700 | 1.6252 | -17.5 | -19.5 | 0.6074 | 2.0312 | -2240.0 | -2064.0 | 1.9609 | 0.1533 |
| 0.0219 | 2.9319 | 2800 | 1.6465 | -17.75 | -19.75 | 0.6055 | 2.0469 | -2272.0 | -2096.0 | 2.0312 | 0.2393 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.3.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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