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---
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: []
---
<!-- 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/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
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