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---
license: apache-2.0
base_model: HuggingFaceTB/SmolLM-135M-Instruct
tags:
- trl
- orpo
- generated_from_trainer
model-index:
- name: ft-orpo-smollm-135M-instruct-on-hf-ultrafeedback
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. -->
# ft-orpo-smollm-135M-instruct-on-hf-ultrafeedback
This model is a fine-tuned version of [HuggingFaceTB/SmolLM-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1646
- Rewards/chosen: -0.1296
- Rewards/rejected: -0.1298
- Rewards/accuracies: 0.4000
- Rewards/margins: 0.0002
- Logps/rejected: -1.2981
- Logps/chosen: -1.2964
- Logits/rejected: 31.6875
- Logits/chosen: 31.3425
- Nll Loss: 1.0873
- Log Odds Ratio: -0.7727
- Log Odds Chosen: -0.0238
## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- 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 | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.4274 | 0.27 | 100 | 1.2066 | -0.1351 | -0.1347 | 0.4100 | -0.0004 | -1.3467 | -1.3508 | 28.6347 | 28.3442 | 1.1292 | -0.7736 | -0.0347 |
| 1.1351 | 0.53 | 200 | 1.1796 | -0.1316 | -0.1316 | 0.4100 | 0.0000 | -1.3162 | -1.3158 | 31.1292 | 30.7764 | 1.1024 | -0.7723 | -0.0251 |
| 1.135 | 0.8 | 300 | 1.1646 | -0.1296 | -0.1298 | 0.4000 | 0.0002 | -1.2981 | -1.2964 | 31.6875 | 31.3425 | 1.0873 | -0.7727 | -0.0238 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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