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---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: mistralit2_1000_STEPS_1e7_rate_03_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. -->
# mistralit2_1000_STEPS_1e7_rate_03_beta_DPO
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6191
- Rewards/chosen: -1.8431
- Rewards/rejected: -2.7054
- Rewards/accuracies: 0.6505
- Rewards/margins: 0.8623
- Logps/rejected: -37.5904
- Logps/chosen: -29.5295
- Logits/rejected: -2.8238
- Logits/chosen: -2.8242
## 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-07
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6777 | 0.1 | 50 | 0.6740 | -0.1496 | -0.1942 | 0.5824 | 0.0446 | -29.2197 | -23.8845 | -2.8632 | -2.8635 |
| 0.6077 | 0.2 | 100 | 0.6364 | -1.2703 | -1.6253 | 0.5846 | 0.3550 | -33.9902 | -27.6202 | -2.8384 | -2.8387 |
| 0.4959 | 0.29 | 150 | 0.6488 | -2.0038 | -2.5512 | 0.5934 | 0.5473 | -37.0763 | -30.0653 | -2.8343 | -2.8347 |
| 0.553 | 0.39 | 200 | 0.5977 | -0.9571 | -1.3986 | 0.6374 | 0.4415 | -33.2344 | -26.5762 | -2.8518 | -2.8521 |
| 0.6334 | 0.49 | 250 | 0.5740 | -0.6757 | -1.1710 | 0.6440 | 0.4953 | -32.4758 | -25.6382 | -2.8479 | -2.8482 |
| 0.5613 | 0.59 | 300 | 0.5961 | -1.4901 | -2.1568 | 0.6374 | 0.6666 | -35.7616 | -28.3529 | -2.8436 | -2.8439 |
| 0.5182 | 0.68 | 350 | 0.6175 | -1.8099 | -2.5639 | 0.6418 | 0.7541 | -37.1189 | -29.4187 | -2.8403 | -2.8407 |
| 0.6292 | 0.78 | 400 | 0.6197 | -1.8949 | -2.6751 | 0.6418 | 0.7802 | -37.4896 | -29.7022 | -2.8352 | -2.8356 |
| 0.6529 | 0.88 | 450 | 0.5986 | -1.3908 | -2.0689 | 0.6527 | 0.6781 | -35.4687 | -28.0218 | -2.8394 | -2.8398 |
| 0.5042 | 0.98 | 500 | 0.5930 | -1.2223 | -1.8903 | 0.6637 | 0.6680 | -34.8735 | -27.4602 | -2.8391 | -2.8395 |
| 0.364 | 1.07 | 550 | 0.5917 | -1.3579 | -2.0905 | 0.6659 | 0.7327 | -35.5409 | -27.9120 | -2.8340 | -2.8344 |
| 0.346 | 1.17 | 600 | 0.6084 | -1.6411 | -2.4313 | 0.6527 | 0.7903 | -36.6769 | -28.8561 | -2.8286 | -2.8291 |
| 0.4524 | 1.27 | 650 | 0.6120 | -1.7303 | -2.5496 | 0.6484 | 0.8192 | -37.0710 | -29.1536 | -2.8265 | -2.8269 |
| 0.3422 | 1.37 | 700 | 0.6172 | -1.7895 | -2.6271 | 0.6505 | 0.8376 | -37.3293 | -29.3507 | -2.8252 | -2.8257 |
| 0.2776 | 1.46 | 750 | 0.6164 | -1.8100 | -2.6641 | 0.6462 | 0.8541 | -37.4528 | -29.4193 | -2.8245 | -2.8249 |
| 0.3599 | 1.56 | 800 | 0.6201 | -1.8360 | -2.6887 | 0.6484 | 0.8527 | -37.5348 | -29.5057 | -2.8241 | -2.8246 |
| 0.4059 | 1.66 | 850 | 0.6205 | -1.8421 | -2.6971 | 0.6440 | 0.8550 | -37.5629 | -29.5263 | -2.8241 | -2.8246 |
| 0.3417 | 1.76 | 900 | 0.6190 | -1.8389 | -2.6983 | 0.6505 | 0.8594 | -37.5666 | -29.5155 | -2.8239 | -2.8243 |
| 0.3409 | 1.86 | 950 | 0.6195 | -1.8423 | -2.7030 | 0.6484 | 0.8606 | -37.5823 | -29.5270 | -2.8237 | -2.8242 |
| 0.2802 | 1.95 | 1000 | 0.6191 | -1.8431 | -2.7054 | 0.6505 | 0.8623 | -37.5904 | -29.5295 | -2.8238 | -2.8242 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
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