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---
library_name: transformers
license: mit
base_model: openai-community/gpt2
tags:
- trl
- dpo
- generated_from_trainer
datasets:
- piqa
model-index:
- name: HW2-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. -->
# HW2-dpo
This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the piqa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8593
- Rewards/chosen: -13.9253
- Rewards/rejected: -15.1905
- Rewards/accuracies: 0.6644
- Rewards/margins: 1.2652
- Logps/rejected: -246.1538
- Logps/chosen: -231.6296
- Logits/rejected: -73.5328
- Logits/chosen: -73.9152
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7148 | 0.2758 | 500 | 0.6866 | -2.4692 | -2.6207 | 0.6073 | 0.1516 | -120.4563 | -117.0685 | -93.4454 | -93.3709 |
| 0.6747 | 0.5516 | 1000 | 0.6612 | -4.3908 | -4.7275 | 0.6495 | 0.3367 | -141.5237 | -136.2848 | -91.8209 | -91.7481 |
| 0.6681 | 0.8275 | 1500 | 0.6704 | -5.5067 | -5.9227 | 0.6439 | 0.4161 | -153.4764 | -147.4433 | -87.9307 | -87.9442 |
| 0.5393 | 1.1033 | 2000 | 0.7086 | -6.7527 | -7.3196 | 0.6501 | 0.5669 | -167.4447 | -159.9034 | -87.8440 | -87.9360 |
| 0.3132 | 1.3791 | 2500 | 0.7451 | -9.5756 | -10.2276 | 0.6520 | 0.6520 | -196.5250 | -188.1325 | -86.2624 | -86.5916 |
| 0.3077 | 1.6549 | 3000 | 0.7269 | -9.8647 | -10.6512 | 0.6514 | 0.7865 | -200.7605 | -191.0236 | -89.7969 | -90.1133 |
| 0.2954 | 1.9308 | 3500 | 0.6959 | -9.1185 | -9.9717 | 0.6725 | 0.8531 | -193.9657 | -183.5620 | -87.1994 | -87.4444 |
| 0.1295 | 2.2066 | 4000 | 0.8306 | -13.7328 | -14.8923 | 0.6650 | 1.1595 | -243.1719 | -229.7044 | -74.6679 | -75.0498 |
| 0.0665 | 2.4824 | 4500 | 0.8662 | -14.5425 | -15.8052 | 0.6600 | 1.2626 | -252.3006 | -237.8021 | -75.1185 | -75.5275 |
| 0.0606 | 2.7582 | 5000 | 0.8593 | -13.9253 | -15.1905 | 0.6644 | 1.2652 | -246.1538 | -231.6296 | -73.5328 | -73.9152 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
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