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Swallow-7b-instruct-v0.1-dpo

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README.md ADDED
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+ ---
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+ license: llama2
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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: tokyotech-llm/Swallow-7b-instruct-v0.1
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+ model-index:
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+ - name: train_logs
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+ results: []
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+ ---
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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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+
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+ # train_logs
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+
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+ This model is a fine-tuned version of [tokyotech-llm/Swallow-7b-instruct-v0.1](https://huggingface.co/tokyotech-llm/Swallow-7b-instruct-v0.1) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6776
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+ - Rewards/chosen: 0.1044
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+ - Rewards/rejected: 0.0678
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+ - Rewards/accuracies: 0.5983
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+ - Rewards/margins: 0.0365
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+ - Logps/rejected: -195.0584
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+ - Logps/chosen: -198.8751
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+ - Logits/rejected: -1.2872
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+ - Logits/chosen: -1.2718
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 4
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+ - seed: 42
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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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+ - training_steps: 300
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+
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+ ### Training results
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+
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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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+ | 0.6922 | 0.0351 | 50 | 0.6910 | -0.0173 | -0.0222 | 0.5433 | 0.0050 | -195.9592 | -200.0917 | -1.3115 | -1.2970 |
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+ | 0.6915 | 0.0702 | 100 | 0.6841 | 0.0935 | 0.0721 | 0.5900 | 0.0214 | -195.0160 | -198.9837 | -1.2971 | -1.2823 |
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+ | 0.6819 | 0.1053 | 150 | 0.6792 | 0.1455 | 0.1116 | 0.5900 | 0.0339 | -194.6210 | -198.4638 | -1.2865 | -1.2708 |
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+ | 0.6825 | 0.1404 | 200 | 0.6784 | 0.1161 | 0.0811 | 0.5933 | 0.0350 | -194.9258 | -198.7577 | -1.2871 | -1.2717 |
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+ | 0.6791 | 0.1754 | 250 | 0.6769 | 0.1049 | 0.0670 | 0.6183 | 0.0378 | -195.0665 | -198.8701 | -1.2885 | -1.2730 |
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+ | 0.6826 | 0.2105 | 300 | 0.6776 | 0.1044 | 0.0678 | 0.5983 | 0.0365 | -195.0584 | -198.8751 | -1.2872 | -1.2718 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.41.0
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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+ "task_type": "CAUSAL_LM",
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+ "use_dora": false,
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+ "use_rslora": false
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+ "bos_token": "<s>",
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+ "chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif false == true and not '<<SYS>>' in messages[0]['content'] %}{% set loop_messages = messages %}{% set system_message = 'あなたは誠実で優秀な日本人のアシスタントです。' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{{ bos_token }}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\\n' + system_message + '\\n<</SYS>>\\n\\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + content.strip() + ' [/INST] ' }}{% elif message['role'] == 'system' %}{{ '<<SYS>>\\n' + content.strip() + '\\n<</SYS>>\\n\\n' }}{% elif message['role'] == 'assistant' %}{{ '' + content.strip() + '' + eos_token }}{% endif %}{% endfor %}",
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