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---
license: llama3
base_model: tsavage68/Summary_L3_1000steps_1e7rate_SFT2
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: Summary_L3_100steps_1e8rate_05beta_CSFTDPO
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. -->
# Summary_L3_100steps_1e8rate_05beta_CSFTDPO
This model is a fine-tuned version of [tsavage68/Summary_L3_1000steps_1e7rate_SFT2](https://huggingface.co/tsavage68/Summary_L3_1000steps_1e7rate_SFT2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6879
- Rewards/chosen: -0.0012
- Rewards/rejected: -0.0138
- Rewards/accuracies: 0.1000
- Rewards/margins: 0.0126
- Logps/rejected: -15.2914
- Logps/chosen: -9.3853
- Logits/rejected: -1.0958
- Logits/chosen: -1.0972
## 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-08
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- 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: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6824 | 0.2004 | 50 | 0.6901 | 0.0066 | -0.0020 | 0.0850 | 0.0086 | -15.2678 | -9.3695 | -1.0960 | -1.0974 |
| 0.6926 | 0.4008 | 100 | 0.6879 | -0.0012 | -0.0138 | 0.1000 | 0.0126 | -15.2914 | -9.3853 | -1.0958 | -1.0972 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
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