Model save
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- trainer_log.jsonl +19 -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: tiiuae/falcon-7b-instruct
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model-index:
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- name: Falcon-7B-Instruct-ORPO
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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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# Falcon-7B-Instruct-ORPO
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This model is a fine-tuned version of [tiiuae/falcon-7b-instruct](https://huggingface.co/tiiuae/falcon-7b-instruct) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5155
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- Rewards/chosen: -0.1444
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- Rewards/rejected: -0.1539
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- Rewards/accuracies: 0.5090
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- Rewards/margins: 0.0095
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- Logps/rejected: -1.5389
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- Logps/chosen: -1.4440
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- Logits/rejected: -14.5432
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- Logits/chosen: -14.4665
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- Sft Loss: 1.4440
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- Odds Ratio Loss: 0.7143
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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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| 1.6309 | 0.8891 | 500 | 1.5816 | -0.1510 | -0.1599 | 0.4940 | 0.0089 | -1.5988 | -1.5096 | -14.4968 | -14.4213 | 1.5096 | 0.7192 |
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| 1.5401 | 1.7782 | 1000 | 1.5269 | -0.1455 | -0.1549 | 0.5020 | 0.0094 | -1.5492 | -1.4555 | -14.5486 | -14.4721 | 1.4555 | 0.7147 |
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| 1.4914 | 2.6673 | 1500 | 1.5155 | -0.1444 | -0.1539 | 0.5090 | 0.0095 | -1.5389 | -1.4440 | -14.5432 | -14.4665 | 1.4440 | 0.7143 |
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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": 1490, "total_steps": 1686, "loss": 1.5003, "accuracy": 0.5062500238418579, "learning_rate": 1.6490167940538343e-07, "epoch": 2.6494776617026004, "percentage": 88.37, "elapsed_time": "5:47:26", "remaining_time": "0:45:42"}
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{"current_steps": 1500, "total_steps": 1686, "loss": 1.4914, "accuracy": 0.48124998807907104, "learning_rate": 1.4866882516191339e-07, "epoch": 2.6672593909757722, "percentage": 88.97, "elapsed_time": "5:50:45", "remaining_time": "0:43:29"}
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{"current_steps": 1500, "total_steps": 1686, "eval_loss": 1.5154520273208618, "epoch": 2.6672593909757722, "percentage": 88.97, "elapsed_time": "5:57:37", "remaining_time": "0:44:20"}
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{"current_steps": 1490, "total_steps": 1686, "loss": 1.5003, "accuracy": 0.5062500238418579, "learning_rate": 1.6490167940538343e-07, "epoch": 2.6494776617026004, "percentage": 88.37, "elapsed_time": "5:47:26", "remaining_time": "0:45:42"}
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{"current_steps": 1500, "total_steps": 1686, "loss": 1.4914, "accuracy": 0.48124998807907104, "learning_rate": 1.4866882516191339e-07, "epoch": 2.6672593909757722, "percentage": 88.97, "elapsed_time": "5:50:45", "remaining_time": "0:43:29"}
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{"current_steps": 1500, "total_steps": 1686, "eval_loss": 1.5154520273208618, "epoch": 2.6672593909757722, "percentage": 88.97, "elapsed_time": "5:57:37", "remaining_time": "0:44:20"}
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{"current_steps": 1520, "total_steps": 1686, "loss": 1.4794, "accuracy": 0.4749999940395355, "learning_rate": 1.1865786358165737e-07, "epoch": 2.702822849522116, "percentage": 90.15, "elapsed_time": "6:03:55", "remaining_time": "0:39:44"}
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