Model save
Browse files- README.md +18 -11
- adapter_config.json +4 -4
- adapter_model.safetensors +1 -1
- all_results.json +17 -17
- eval_results.json +13 -13
- runs/Mar08_12-18-16_cccxc542/events.out.tfevents.1709918369.cccxc542.189796.0 +3 -0
- runs/Mar08_12-24-55_cccxc542/events.out.tfevents.1709918735.cccxc542.206115.0 +3 -0
- runs/Mar08_12-24-55_cccxc542/events.out.tfevents.1709919790.cccxc542.206115.1 +3 -0
- train_results.json +5 -5
- trainer_state.json +80 -10
- training_args.bin +1 -1
README.md
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license: apache-2.0
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library_name: peft
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tags:
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- alignment-handbook
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- trl
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- dpo
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- generated_from_trainer
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- trl
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- dpo
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- alignment-handbook
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- generated_from_trainer
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datasets:
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- HuggingFaceH4/ultrafeedback_binarized
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base_model: mistralai/Mistral-7B-v0.1
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model-index:
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- name: zephyr-7b-dpo-qlora-fsdp
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# zephyr-7b-dpo-qlora-fsdp
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This model is a fine-tuned version of [
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## Model description
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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:
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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: 4
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- total_train_batch_size:
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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:
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### Framework versions
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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: mistralai/Mistral-7B-v0.1
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model-index:
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- name: zephyr-7b-dpo-qlora-fsdp
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# zephyr-7b-dpo-qlora-fsdp
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6865
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- Rewards/chosen: 0.0331
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- Rewards/rejected: 0.0188
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- Rewards/accuracies: 0.5935
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- Rewards/margins: 0.0143
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- Logps/rejected: -257.1393
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- Logps/chosen: -276.4896
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- Logits/rejected: -2.3640
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- Logits/chosen: -2.4104
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## Model description
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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: 5
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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: 4
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- total_train_batch_size: 20
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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: 0.01
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### Training results
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### Framework versions
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adapter_config.json
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"target_modules": [
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"gate_proj",
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"k_proj"
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"task_type": "CAUSAL_LM",
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