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---
base_model: loubnabnl/smollm2-360M-8k-lc100k-mix1-ep2
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: smollm2-360M-8k-lc100k-dpo-ultaf-ep2
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/loubnabnl/huggingface/runs/3nedrmyg)
# smollm2-360M-8k-lc100k-dpo-ultaf-ep2
This model is a fine-tuned version of [loubnabnl/smollm2-360M-8k-lc100k-mix1-ep2](https://huggingface.co./loubnabnl/smollm2-360M-8k-lc100k-mix1-ep2) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6348
- Rewards/chosen: -0.0342
- Rewards/rejected: -0.3910
- Rewards/accuracies: 0.6190
- Rewards/margins: 0.3568
- Logps/rejected: -323.7198
- Logps/chosen: -375.6464
- Logits/rejected: -1.6969
- Logits/chosen: -1.6408
## 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-06
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7098 | 0.2094 | 100 | 0.7162 | -0.0109 | -0.0675 | 0.5278 | 0.0566 | -323.0727 | -375.5997 | -1.6983 | -1.6387 |
| 0.6825 | 0.4187 | 200 | 0.6842 | -0.0010 | -0.1880 | 0.5794 | 0.1870 | -323.3139 | -375.5800 | -1.6938 | -1.6358 |
| 0.663 | 0.6281 | 300 | 0.6617 | 0.0225 | -0.2389 | 0.6032 | 0.2614 | -323.4156 | -375.5330 | -1.6893 | -1.6317 |
| 0.6547 | 0.8375 | 400 | 0.6591 | 0.0001 | -0.3516 | 0.6389 | 0.3517 | -323.6410 | -375.5778 | -1.6980 | -1.6414 |
| 0.6456 | 1.0468 | 500 | 0.6430 | 0.0133 | -0.3566 | 0.6667 | 0.3699 | -323.6510 | -375.5514 | -1.6931 | -1.6365 |
| 0.6054 | 1.2562 | 600 | 0.6423 | -0.0329 | -0.3895 | 0.6349 | 0.3566 | -323.7167 | -375.6438 | -1.6991 | -1.6431 |
| 0.6129 | 1.4656 | 700 | 0.6431 | -0.0449 | -0.4183 | 0.6349 | 0.3735 | -323.7745 | -375.6677 | -1.6979 | -1.6414 |
| 0.5972 | 1.6750 | 800 | 0.6384 | -0.0695 | -0.4139 | 0.6429 | 0.3444 | -323.7656 | -375.7169 | -1.6965 | -1.6399 |
| 0.6207 | 1.8843 | 900 | 0.6362 | -0.0627 | -0.4222 | 0.6786 | 0.3595 | -323.7822 | -375.7033 | -1.6976 | -1.6407 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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