Model save
Browse files- README.md +73 -0
- adapter_model.safetensors +1 -1
- all_results.json +21 -0
- eval_results.json +16 -0
- runs/Jan17_07-21-05_hrsung-a100/events.out.tfevents.1705476496.hrsung-a100.134878.0 +2 -2
- runs/Jan17_07-21-05_hrsung-a100/events.out.tfevents.1705536818.hrsung-a100.134878.1 +3 -0
- train_results.json +8 -0
- trainer_state.json +0 -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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- generated_from_trainer
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base_model: alignment-handbook/zephyr-7b-sft-full
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model-index:
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- name: zephyr-7b-dpo-lora-pubmedqa-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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# zephyr-7b-dpo-lora-pubmedqa-ultrafeedback
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This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5835
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- Rewards/chosen: -0.1486
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- Rewards/rejected: -0.4853
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- Rewards/accuracies: 0.7105
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- Rewards/margins: 0.3368
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- Logps/rejected: -314.4243
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- Logps/chosen: -302.0460
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- Logits/rejected: -2.5375
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- Logits/chosen: -2.5889
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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: 4
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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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: 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 |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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| 0.5703 | 0.92 | 7000 | 0.5835 | -0.1500 | -0.4872 | 0.7140 | 0.3372 | -314.6089 | -302.1864 | -2.5236 | -2.5765 |
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### Framework versions
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- PEFT 0.7.1
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- Transformers 4.36.2
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- Pytorch 2.1.1+cu121
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- Datasets 2.14.6
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- Tokenizers 0.15.0
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adapter_model.safetensors
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all_results.json
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{
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"epoch": 1.0,
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"eval_logits/chosen": -2.5889480113983154,
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"eval_logits/rejected": -2.5375468730926514,
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"eval_logps/chosen": -302.0460205078125,
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"eval_logps/rejected": -314.4243469238281,
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"eval_loss": 0.5835465788841248,
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"eval_rewards/accuracies": 0.7105000019073486,
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"eval_rewards/chosen": -0.1485649198293686,
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"eval_rewards/margins": 0.33676549792289734,
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"eval_rewards/rejected": -0.4853304326534271,
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"eval_runtime": 1163.5942,
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"eval_samples": 2000,
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"eval_samples_per_second": 1.719,
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"eval_steps_per_second": 0.215,
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"train_loss": 0.6024045768410584,
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"train_runtime": 59158.061,
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"train_samples": 61135,
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"train_samples_per_second": 1.033,
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"train_steps_per_second": 0.129
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}
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eval_results.json
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{
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"epoch": 1.0,
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"eval_logits/chosen": -2.5889480113983154,
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"eval_logits/rejected": -2.5375468730926514,
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"eval_logps/chosen": -302.0460205078125,
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"eval_logps/rejected": -314.4243469238281,
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"eval_loss": 0.5835465788841248,
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"eval_rewards/accuracies": 0.7105000019073486,
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"eval_rewards/chosen": -0.1485649198293686,
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"eval_rewards/margins": 0.33676549792289734,
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"eval_rewards/rejected": -0.4853304326534271,
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"eval_runtime": 1163.5942,
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"eval_samples": 2000,
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"eval_samples_per_second": 1.719,
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"eval_steps_per_second": 0.215
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}
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runs/Jan17_07-21-05_hrsung-a100/events.out.tfevents.1705476496.hrsung-a100.134878.0
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runs/Jan17_07-21-05_hrsung-a100/events.out.tfevents.1705536818.hrsung-a100.134878.1
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train_results.json
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{
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"epoch": 1.0,
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"train_loss": 0.6024045768410584,
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"train_runtime": 59158.061,
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"train_samples": 61135,
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"train_samples_per_second": 1.033,
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"train_steps_per_second": 0.129
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}
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trainer_state.json
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