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---
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: MedQA_L3_450steps_1e7rate_03beta_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. -->
# MedQA_L3_450steps_1e7rate_03beta_CSFTDPO
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6479
- Rewards/chosen: 0.1876
- Rewards/rejected: 0.0690
- Rewards/accuracies: 0.6637
- Rewards/margins: 0.1186
- Logps/rejected: -21.0864
- Logps/chosen: -17.5973
- Logits/rejected: -0.9362
- Logits/chosen: -0.9357
## 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: 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: 450
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6938 | 0.0489 | 50 | 0.6934 | 0.0041 | 0.0042 | 0.5099 | -0.0000 | -21.3026 | -18.2088 | -0.9262 | -0.9257 |
| 0.6807 | 0.0977 | 100 | 0.6781 | 0.1130 | 0.0788 | 0.6110 | 0.0343 | -21.0540 | -17.8459 | -0.9280 | -0.9275 |
| 0.6689 | 0.1466 | 150 | 0.6622 | 0.1706 | 0.0922 | 0.6286 | 0.0784 | -21.0091 | -17.6540 | -0.9313 | -0.9308 |
| 0.6589 | 0.1954 | 200 | 0.6569 | 0.1748 | 0.0827 | 0.6462 | 0.0921 | -21.0408 | -17.6401 | -0.9339 | -0.9334 |
| 0.6798 | 0.2443 | 250 | 0.6507 | 0.1854 | 0.0751 | 0.6505 | 0.1103 | -21.0663 | -17.6047 | -0.9352 | -0.9347 |
| 0.6402 | 0.2931 | 300 | 0.6482 | 0.1927 | 0.0761 | 0.6725 | 0.1166 | -21.0627 | -17.5802 | -0.9358 | -0.9352 |
| 0.7088 | 0.3420 | 350 | 0.6481 | 0.1883 | 0.0698 | 0.6637 | 0.1185 | -21.0838 | -17.5951 | -0.9357 | -0.9352 |
| 0.6301 | 0.3908 | 400 | 0.6487 | 0.1878 | 0.0712 | 0.6549 | 0.1166 | -21.0792 | -17.5965 | -0.9361 | -0.9356 |
| 0.6454 | 0.4397 | 450 | 0.6479 | 0.1876 | 0.0690 | 0.6637 | 0.1186 | -21.0864 | -17.5973 | -0.9362 | -0.9357 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.0.0+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
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