Model save
Browse files- README.md +25 -26
- adapter_config.json +3 -3
- adapter_model.safetensors +1 -1
- all_results.json +16 -16
- eval_results.json +12 -12
- train_results.json +4 -4
- trainer_state.json +581 -1331
- training_args.bin +1 -1
README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name: zephyr-7b-dpo-qlora
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results: []
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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 the None dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Rewards/chosen:
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- Rewards/rejected: -
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- Rewards/accuracies: 0.
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- Rewards/margins:
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- Logps/rejected: -
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- Logps/chosen: -
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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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- num_devices: 4
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- gradient_accumulation_steps:
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- total_train_batch_size:
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- total_eval_batch_size: 32
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen |
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| 0.0182 | 0.52 | 500 | 0.0148 | -331.5956 | -289.6645 | 0.4464 | -41.9311 | -29219.6113 | -33432.5625 | 256.0 | 0.0 |
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| 0.013 | 0.63 | 600 | 0.0143 | -356.6841 | -312.4188 | 0.4544 | -44.2654 | -31495.0312 | -35941.4141 | 256.0 | 0.0 |
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| 0.0165 | 0.73 | 700 | 0.0143 | -353.6940 | -310.5345 | 0.4504 | -43.1595 | -31306.6094 | -35642.4023 | 256.0 | 0.0 |
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| 0.0145 | 0.84 | 800 | 0.0135 | -374.0797 | -328.2772 | 0.4544 | -45.8026 | -33080.8789 | -37680.9766 | 256.0 | 0.0 |
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| 0.0195 | 0.94 | 900 | 0.0137 | -376.5184 | -330.4032 | 0.4544 | -46.1152 | -33293.4727 | -37924.8398 | 256.0 | 0.0 |
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### Framework versions
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- Pytorch 2.1.1+cu121
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- Datasets 2.14.6
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- Tokenizers 0.
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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: mistralai/Mistral-7B-v0.1
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model-index:
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- name: zephyr-7b-dpo-qlora
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results: []
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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 the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2121.0452
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- Rewards/chosen: 0.0578
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- Rewards/rejected: -0.0912
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- Rewards/accuracies: 0.7599
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- Rewards/margins: 0.1490
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- Logps/rejected: -253.8891
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- Logps/chosen: -259.2458
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- Logits/rejected: -2.2028
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- Logits/chosen: -2.2552
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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: 2
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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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- num_devices: 4
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 128
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- total_eval_batch_size: 32
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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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### 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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| 2149.4746 | 0.21 | 100 | 2190.7666 | 0.0445 | -0.0848 | 0.7460 | 0.1293 | -253.2523 | -260.5782 | -2.1770 | -2.2229 |
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| 2105.1256 | 0.42 | 200 | 2151.1555 | 0.0543 | -0.0961 | 0.7599 | 0.1504 | -254.3840 | -259.5941 | -2.2074 | -2.2603 |
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| 2135.4973 | 0.63 | 300 | 2129.0896 | 0.0626 | -0.0799 | 0.7560 | 0.1425 | -252.7585 | -258.7624 | -2.2232 | -2.2765 |
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| 2099.8018 | 0.84 | 400 | 2121.6672 | 0.0538 | -0.0959 | 0.7540 | 0.1497 | -254.3591 | -259.6440 | -2.2016 | -2.2541 |
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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 0.15.2
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adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"gate_proj",
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"up_proj",
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"k_proj",
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"down_proj",
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"o_proj",
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"task_type": "CAUSAL_LM"
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"down_proj",
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"task_type": "CAUSAL_LM"
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}
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adapter_model.safetensors
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all_results.json
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