---
base_model: loubnabnl/smollm2-1.7B-8k-mix7-ep2-v2
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: smollm2-1.7B-8k-mix7-ep2-v2-dpo-ultraf-ep3
  results: []
---

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[<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/n6jjrqmx)
# smollm2-1.7B-8k-mix7-ep2-v2-dpo-ultraf-ep3

This model is a fine-tuned version of [loubnabnl/smollm2-1.7B-8k-mix7-ep2-v2](https://huggingface.co/loubnabnl/smollm2-1.7B-8k-mix7-ep2-v2) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5878
- Rewards/chosen: 0.0167
- Rewards/rejected: -0.5739
- Rewards/accuracies: 0.6746
- Rewards/margins: 0.5907
- Logps/rejected: -275.4315
- Logps/chosen: -310.2510
- Logits/rejected: -0.3685
- Logits/chosen: -0.3410

## 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6787        | 0.2094 | 100  | 0.6967          | 0.0159         | -0.0702          | 0.5516             | 0.0861          | -274.4240      | -310.2527    | -0.3377         | -0.3141       |
| 0.645         | 0.4187 | 200  | 0.6491          | -0.0498        | -0.3020          | 0.6032             | 0.2523          | -274.8876      | -310.3840    | -0.3463         | -0.3229       |
| 0.6161        | 0.6281 | 300  | 0.6316          | -0.0637        | -0.4218          | 0.6825             | 0.3581          | -275.1272      | -310.4119    | -0.3552         | -0.3317       |
| 0.5964        | 0.8375 | 400  | 0.6100          | -0.0166        | -0.4381          | 0.6587             | 0.4215          | -275.1597      | -310.3176    | -0.3545         | -0.3291       |
| 0.5394        | 1.0468 | 500  | 0.6066          | -0.0098        | -0.4749          | 0.7103             | 0.4651          | -275.2332      | -310.3040    | -0.3576         | -0.3320       |
| 0.5099        | 1.2562 | 600  | 0.6007          | -0.0192        | -0.5329          | 0.6786             | 0.5137          | -275.3493      | -310.3229    | -0.3635         | -0.3380       |
| 0.5056        | 1.4656 | 700  | 0.5876          | -0.0630        | -0.5941          | 0.6905             | 0.5311          | -275.4717      | -310.4104    | -0.3672         | -0.3407       |
| 0.4936        | 1.6750 | 800  | 0.5994          | -0.0296        | -0.5590          | 0.6746             | 0.5294          | -275.4016      | -310.3437    | -0.3658         | -0.3384       |
| 0.4904        | 1.8843 | 900  | 0.5989          | -0.0581        | -0.6149          | 0.6944             | 0.5568          | -275.5134      | -310.4006    | -0.3705         | -0.3443       |
| 0.4622        | 2.0937 | 1000 | 0.5939          | -0.0662        | -0.6068          | 0.6944             | 0.5405          | -275.4971      | -310.4169    | -0.3724         | -0.3450       |
| 0.4458        | 2.3031 | 1100 | 0.5923          | -0.0536        | -0.6393          | 0.6944             | 0.5857          | -275.5622      | -310.3918    | -0.3728         | -0.3450       |
| 0.4462        | 2.5124 | 1200 | 0.5894          | -0.0486        | -0.6300          | 0.7024             | 0.5814          | -275.5435      | -310.3816    | -0.3710         | -0.3432       |
| 0.4312        | 2.7218 | 1300 | 0.5861          | -0.0751        | -0.6393          | 0.6667             | 0.5642          | -275.5621      | -310.4347    | -0.3724         | -0.3442       |
| 0.4454        | 2.9312 | 1400 | 0.5942          | -0.0056        | -0.5970          | 0.6944             | 0.5914          | -275.4775      | -310.2956    | -0.3681         | -0.3401       |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1