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---
license: apache-2.0
base_model: mosaicml/mpt-7b-instruct
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: mpt_1000_STEPS_1e5_rate_05_beta_DPO
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. -->
# mpt_1000_STEPS_1e5_rate_05_beta_DPO
This model is a fine-tuned version of [mosaicml/mpt-7b-instruct](https://huggingface.co/mosaicml/mpt-7b-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1807
- Rewards/chosen: -19.4532
- Rewards/rejected: -19.2274
- Rewards/accuracies: 0.5033
- Rewards/margins: -0.2258
- Logps/rejected: -60.0122
- Logps/chosen: -59.6986
- Logits/rejected: 7.5623
- Logits/chosen: 7.5620
## 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-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 1.5203 | 0.05 | 50 | 1.5171 | -1.5689 | -1.4986 | 0.4791 | -0.0703 | -24.5546 | -23.9299 | 14.9602 | 14.9630 |
| 4.4339 | 0.1 | 100 | 2.9117 | -11.0118 | -10.8837 | 0.4813 | -0.1281 | -43.3247 | -42.8158 | 22.8545 | 22.8566 |
| 5.6756 | 0.15 | 150 | 4.3519 | -20.9772 | -20.5347 | 0.4703 | -0.4424 | -62.6269 | -62.7465 | 13.8454 | 13.8456 |
| 3.4587 | 0.2 | 200 | 3.7953 | -20.5135 | -19.9733 | 0.4549 | -0.5402 | -61.5040 | -61.8193 | 9.3162 | 9.3161 |
| 3.1326 | 0.24 | 250 | 4.2192 | -16.2805 | -16.0169 | 0.4857 | -0.2636 | -53.5912 | -53.3533 | 17.4741 | 17.4741 |
| 4.3129 | 0.29 | 300 | 3.2442 | -18.6648 | -18.0875 | 0.4462 | -0.5773 | -57.7325 | -58.1219 | 9.3299 | 9.3300 |
| 4.1056 | 0.34 | 350 | 3.0391 | -19.9243 | -19.4698 | 0.4659 | -0.4545 | -60.4970 | -60.6408 | 13.8852 | 13.8856 |
| 3.4604 | 0.39 | 400 | 3.0915 | -16.3912 | -16.0366 | 0.5055 | -0.3546 | -53.6306 | -53.5745 | 9.7129 | 9.7125 |
| 4.7084 | 0.44 | 450 | 2.7841 | -18.9738 | -18.6116 | 0.4835 | -0.3622 | -58.7806 | -58.7398 | 9.9158 | 9.9143 |
| 4.1944 | 0.49 | 500 | 2.9877 | -22.1479 | -21.8535 | 0.4901 | -0.2944 | -65.2644 | -65.0879 | 10.6479 | 10.6476 |
| 3.8283 | 0.54 | 550 | 2.4650 | -19.8299 | -19.7039 | 0.4989 | -0.1260 | -60.9653 | -60.4520 | 5.6892 | 5.6889 |
| 3.2208 | 0.59 | 600 | 2.3549 | -15.6227 | -15.7624 | 0.5385 | 0.1397 | -53.0822 | -52.0377 | 11.5783 | 11.5782 |
| 2.1741 | 0.64 | 650 | 2.4777 | -19.7204 | -19.3976 | 0.4945 | -0.3228 | -60.3526 | -60.2330 | 10.8601 | 10.8596 |
| 2.8376 | 0.68 | 700 | 2.4241 | -18.3119 | -18.1735 | 0.5055 | -0.1384 | -57.9045 | -57.4161 | 8.0859 | 8.0854 |
| 2.4514 | 0.73 | 750 | 2.2743 | -20.2330 | -20.0266 | 0.5033 | -0.2064 | -61.6106 | -61.2582 | 6.6227 | 6.6223 |
| 1.8899 | 0.78 | 800 | 2.2326 | -19.6323 | -19.3966 | 0.5121 | -0.2358 | -60.3506 | -60.0568 | 7.6793 | 7.6789 |
| 2.435 | 0.83 | 850 | 2.1976 | -19.5253 | -19.2881 | 0.5121 | -0.2372 | -60.1336 | -59.8427 | 7.3698 | 7.3695 |
| 2.7112 | 0.88 | 900 | 2.1806 | -19.4443 | -19.2182 | 0.5011 | -0.2261 | -59.9939 | -59.6808 | 7.5579 | 7.5575 |
| 2.6506 | 0.93 | 950 | 2.1819 | -19.4556 | -19.2275 | 0.5011 | -0.2280 | -60.0125 | -59.7034 | 7.5627 | 7.5623 |
| 1.5392 | 0.98 | 1000 | 2.1807 | -19.4532 | -19.2274 | 0.5033 | -0.2258 | -60.0122 | -59.6986 | 7.5623 | 7.5620 |
### Framework versions
- Transformers 4.39.1
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
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