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---
base_model: lvwerra/gpt2-imdb
tags:
- generated_from_trainer
model-index:
- name: training
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. -->
# training
This model is a fine-tuned version of [lvwerra/gpt2-imdb](https://huggingface.co/lvwerra/gpt2-imdb) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4649
- Rewards/chosen: 1.1097
- Rewards/rejected: 0.3323
- Rewards/accuracies: 0.8186
- Rewards/margins: 0.7774
- Logps/rejected: -143.4800
- Logps/chosen: -175.0714
- Logits/rejected: -35.2043
- Logits/chosen: -32.7114
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| No log | 0.55 | 400 | 0.6593 | 1.0074 | 0.5904 | 0.7357 | 0.4170 | -140.8990 | -176.0949 | -35.9356 | -33.1922 |
| 0.7974 | 1.11 | 800 | 0.5807 | 1.1511 | 0.5902 | 0.7634 | 0.5610 | -140.9016 | -174.6575 | -35.9192 | -33.2655 |
| 0.5983 | 1.66 | 1200 | 0.5200 | 1.0697 | 0.4300 | 0.7979 | 0.6397 | -142.5030 | -175.4720 | -35.5696 | -33.0300 |
| 0.4982 | 2.21 | 1600 | 0.4807 | 1.1128 | 0.3733 | 0.8158 | 0.7395 | -143.0704 | -175.0409 | -35.2967 | -32.7791 |
| 0.4663 | 2.77 | 2000 | 0.4649 | 1.1097 | 0.3323 | 0.8186 | 0.7774 | -143.4800 | -175.0714 | -35.2043 | -32.7114 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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