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---
library_name: transformers
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: Llama0-3-8b-v0.1-p-0.05-lr6e-7-e1
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. -->
# Llama0-3-8b-v0.1-p-0.05-lr6e-7-e1
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: 0.6348
- Rewards/chosen: -0.7856
- Rewards/rejected: -0.8817
- Rewards/accuracies: 0.5766
- Rewards/margins: 0.0961
- Logps/rejected: -174.9295
- Logps/chosen: -166.8561
- Logits/rejected: 0.2248
- Logits/chosen: 0.2123
## 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: 6e-07
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6639 | 0.2137 | 100 | 0.6632 | -0.0650 | -0.0751 | 0.5968 | 0.0101 | -94.2649 | -94.7914 | 0.0767 | 0.0572 |
| 0.6507 | 0.4275 | 200 | 0.6492 | -0.2974 | -0.3355 | 0.6008 | 0.0381 | -120.3051 | -118.0318 | 0.1386 | 0.1215 |
| 0.6383 | 0.6412 | 300 | 0.6397 | -0.6120 | -0.6852 | 0.5887 | 0.0732 | -155.2713 | -149.4875 | 0.2203 | 0.2063 |
| 0.6362 | 0.8549 | 400 | 0.6356 | -0.7457 | -0.8367 | 0.5766 | 0.0910 | -170.4306 | -162.8660 | 0.2216 | 0.2081 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.20.0
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