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--- |
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license: apache-2.0 |
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base_model: tsavage68/UTI_M2_1000steps_1e7rate_SFT |
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tags: |
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- trl |
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- dpo |
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- generated_from_trainer |
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model-index: |
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- name: UTI2_M2_50steps_1e6rate_01beta_CSFTDPO |
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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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# UTI2_M2_50steps_1e6rate_01beta_CSFTDPO |
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This model is a fine-tuned version of [tsavage68/UTI_M2_1000steps_1e7rate_SFT](https://huggingface.co/tsavage68/UTI_M2_1000steps_1e7rate_SFT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5476 |
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- Rewards/chosen: -0.0191 |
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- Rewards/rejected: -2.0342 |
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- Rewards/accuracies: 0.2100 |
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- Rewards/margins: 2.0151 |
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- Logps/rejected: -29.7161 |
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- Logps/chosen: -4.7332 |
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- Logits/rejected: -2.5508 |
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- Logits/chosen: -2.5517 |
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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: 1e-06 |
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- train_batch_size: 2 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 50 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.6238 | 0.3333 | 25 | 0.6989 | 0.0094 | -1.0339 | 0.1900 | 1.0433 | -19.7134 | -4.4489 | -2.5742 | -2.5732 | |
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| 0.6671 | 0.6667 | 50 | 0.5476 | -0.0191 | -2.0342 | 0.2100 | 2.0151 | -29.7161 | -4.7332 | -2.5508 | -2.5517 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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