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---
license: llama2
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: llama-2-nl/Llama-2-7b-hf-lora-original-sft
datasets:
- BramVanroy/ultra_feedback_dutch
model-index:
- name: Llama-2-7b-hf-lora-original-it
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. -->
# Llama-2-7b-hf-lora-original-it
This model is a fine-tuned version of [llama-2-nl/Llama-2-7b-hf-lora-original-sft](https://huggingface.co/llama-2-nl/Llama-2-7b-hf-lora-original-sft) on the BramVanroy/ultra_feedback_dutch dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3536
- Rewards/chosen: 0.1143
- Rewards/rejected: -0.9295
- Rewards/accuracies: 0.9396
- Rewards/margins: 1.0437
- Logps/rejected: -547.4578
- Logps/chosen: -600.8353
- Logits/rejected: -0.8732
- Logits/chosen: -0.9594
## 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-07
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5984 | 0.1327 | 100 | 0.5904 | 0.0549 | -0.1735 | 0.9030 | 0.2283 | -539.8975 | -601.4293 | -1.1606 | -1.1395 |
| 0.4622 | 0.2653 | 200 | 0.4581 | 0.1134 | -0.4980 | 0.9351 | 0.6113 | -543.1426 | -600.8441 | -1.2714 | -1.2180 |
| 0.3934 | 0.3980 | 300 | 0.3959 | 0.1263 | -0.7212 | 0.9366 | 0.8475 | -545.3747 | -600.7144 | -1.0528 | -1.0755 |
| 0.3629 | 0.5307 | 400 | 0.3674 | 0.1170 | -0.8608 | 0.9381 | 0.9777 | -546.7705 | -600.8080 | -1.1109 | -1.1154 |
| 0.3556 | 0.6633 | 500 | 0.3561 | 0.1136 | -0.9146 | 0.9388 | 1.0282 | -547.3090 | -600.8419 | -0.8266 | -0.9289 |
| 0.3488 | 0.7960 | 600 | 0.3540 | 0.1104 | -0.9310 | 0.9410 | 1.0415 | -547.4734 | -600.8737 | -1.0676 | -1.0877 |
| 0.3563 | 0.9287 | 700 | 0.3540 | 0.1166 | -0.9259 | 0.9396 | 1.0425 | -547.4224 | -600.8121 | -0.8736 | -0.9600 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.1.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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