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--- |
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license: apache-2.0 |
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base_model: HuggingFaceTB/SmolLM-135M-Instruct |
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tags: |
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- trl |
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- orpo |
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- generated_from_trainer |
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model-index: |
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- name: ft-orpo-smollm-135M-instruct-on-hf-ultrafeedback |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ft-orpo-smollm-135M-instruct-on-hf-ultrafeedback |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1646 |
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- Rewards/chosen: -0.1296 |
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- Rewards/rejected: -0.1298 |
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- Rewards/accuracies: 0.4000 |
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- Rewards/margins: 0.0002 |
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- Logps/rejected: -1.2981 |
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- Logps/chosen: -1.2964 |
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- Logits/rejected: 31.6875 |
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- Logits/chosen: 31.3425 |
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- Nll Loss: 1.0873 |
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- Log Odds Ratio: -0.7727 |
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- Log Odds Chosen: -0.0238 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| 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 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:| |
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| 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 | |
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| 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 | |
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| 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 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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