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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- trl |
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- orpo |
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- unsloth |
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- generated_from_trainer |
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base_model: cognitivecomputations/dolphin-2.9.1-yi-1.5-9b |
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model-index: |
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- name: Gaston_dolphin-2.9.1-yi-1.5-9b |
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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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[<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/bacoco/Gaston_dolphin-2.9.1-yi-1.5-9b/runs/4d2n86g4) |
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# Gaston_dolphin-2.9.1-yi-1.5-9b |
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This model is a fine-tuned version of [cognitivecomputations/dolphin-2.9.1-yi-1.5-9b](https://huggingface.co/cognitivecomputations/dolphin-2.9.1-yi-1.5-9b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4290 |
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- Rewards/chosen: -0.0153 |
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- Rewards/rejected: -0.2895 |
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- Rewards/accuracies: 0.9985 |
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- Rewards/margins: 0.2742 |
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- Logps/rejected: -2.8952 |
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- Logps/chosen: -0.1528 |
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- Logits/rejected: -0.1534 |
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- Logits/chosen: 0.0002 |
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- Nll Loss: 0.4278 |
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- Log Odds Ratio: -0.0124 |
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- Log Odds Chosen: 4.8981 |
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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: 8e-06 |
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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: 4 |
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- total_train_batch_size: 16 |
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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_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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| 0.5193 | 0.1005 | 103 | 0.5159 | -0.0187 | -0.0825 | 0.9971 | 0.0638 | -0.8248 | -0.1866 | 0.1547 | 0.1467 | 0.5004 | -0.1555 | 2.0327 | |
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| 0.4988 | 0.2009 | 206 | 0.4724 | -0.0170 | -0.1413 | 0.9985 | 0.1243 | -1.4130 | -0.1703 | 0.0154 | -0.0134 | 0.4661 | -0.0627 | 3.0432 | |
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| 0.4375 | 0.3014 | 309 | 0.4577 | -0.0162 | -0.1628 | 0.9985 | 0.1466 | -1.6283 | -0.1622 | 0.1372 | 0.1328 | 0.4530 | -0.0467 | 3.3955 | |
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| 0.4738 | 0.4019 | 412 | 0.4463 | -0.0160 | -0.2198 | 0.9985 | 0.2038 | -2.1980 | -0.1596 | -0.0220 | 0.0649 | 0.4438 | -0.0250 | 4.0928 | |
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| 0.4893 | 0.5023 | 515 | 0.4406 | -0.0159 | -0.2499 | 0.9985 | 0.2341 | -2.4993 | -0.1585 | -0.0720 | 0.0474 | 0.4388 | -0.0185 | 4.4389 | |
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| 0.4565 | 0.6028 | 618 | 0.4357 | -0.0157 | -0.3289 | 0.9985 | 0.3133 | -3.2895 | -0.1566 | -0.1392 | 0.0470 | 0.4347 | -0.0093 | 5.2916 | |
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| 0.4069 | 0.7032 | 721 | 0.4324 | -0.0154 | -0.3096 | 0.9985 | 0.2942 | -3.0962 | -0.1544 | -0.1833 | -0.0044 | 0.4313 | -0.0107 | 5.1028 | |
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| 0.4297 | 0.8037 | 824 | 0.4299 | -0.0153 | -0.2854 | 0.9985 | 0.2701 | -2.8536 | -0.1528 | -0.1911 | -0.0397 | 0.4286 | -0.0129 | 4.8536 | |
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| 0.4437 | 0.9042 | 927 | 0.4290 | -0.0153 | -0.2895 | 0.9985 | 0.2742 | -2.8952 | -0.1528 | -0.1534 | 0.0002 | 0.4278 | -0.0124 | 4.8981 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
