Model save
Browse files- README.md +77 -0
- trainer_log.jsonl +28 -0
README.md
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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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- dpo
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- llama-factory
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- generated_from_trainer
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base_model: mistralai/Mistral-7B-Instruct-v0.3
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model-index:
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- name: Mistral-7B-Instruct-v0.3-ORPO-SALT-HALF
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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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# Mistral-7B-Instruct-v0.3-ORPO-SALT-HALF
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8506
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- Rewards/chosen: -0.0787
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- Rewards/rejected: -0.0996
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- Rewards/accuracies: 0.5724
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- Rewards/margins: 0.0209
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- Logps/rejected: -0.9956
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- Logps/chosen: -0.7867
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- Logits/rejected: -3.1507
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- Logits/chosen: -3.1305
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- Sft Loss: 0.7867
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- Odds Ratio Loss: 0.6382
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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: 5e-06
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 8
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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_steps: 0.1
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- num_epochs: 3.0
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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 | Sft Loss | Odds Ratio Loss |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
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| 0.8758 | 0.8467 | 500 | 0.8691 | -0.0805 | -0.1009 | 0.5705 | 0.0203 | -1.0086 | -0.8054 | -3.1276 | -3.1089 | 0.8054 | 0.6371 |
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| 0.8098 | 1.6935 | 1000 | 0.8549 | -0.0791 | -0.0999 | 0.5676 | 0.0207 | -0.9985 | -0.7911 | -3.1170 | -3.0966 | 0.7911 | 0.6375 |
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| 0.8135 | 2.5402 | 1500 | 0.8506 | -0.0787 | -0.0996 | 0.5724 | 0.0209 | -0.9956 | -0.7867 | -3.1507 | -3.1305 | 0.7867 | 0.6382 |
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.40.1
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- Pytorch 2.3.0
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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trainer_log.jsonl
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{"current_steps": 1500, "total_steps": 1770, "loss": 0.8135, "accuracy": 0.581250011920929, "learning_rate": 2.8165102503600716e-07, "epoch": 2.5402201524132093, "percentage": 84.75, "elapsed_time": "4:07:23", "remaining_time": "0:44:31"}
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{"current_steps": 1500, "total_steps": 1770, "eval_loss": 0.8505691885948181, "epoch": 2.5402201524132093, "percentage": 84.75, "elapsed_time": "4:10:38", "remaining_time": "0:45:06"}
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{"current_steps": 1490, "total_steps": 1770, "loss": 0.8252, "accuracy": 0.574999988079071, "learning_rate": 3.024615823368371e-07, "epoch": 2.523285351397121, "percentage": 84.18, "elapsed_time": "4:05:47", "remaining_time": "0:46:11"}
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