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--- |
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library_name: transformers |
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license: |
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- llama3.1 |
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- gemma |
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base_model: google/gemma-2-27b |
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tags: |
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- axolotl |
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- generated_from_trainer |
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--- |
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# Llama-Gemma-2-27b-SFT-trial1 |
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## 概要 |
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[google/gemma-2-27b](https://huggingface.co/google/gemma-2-27b)を教師あり学習によりInstruction Tuningしたモデルです。 |
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[松尾研大規模言語モデル講座2024](https://weblab.t.u-tokyo.ac.jp/lecture/course-list/large-language-model/)のコンペ用の提出モデル作成の一環として作成・公開しています。 |
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This model is built with Llama and Qwen. |
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## 使用データセット |
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- [Aratako/Magpie-Tanuki-Qwen2.5-72B-Answered](https://huggingface.co/datasets/Aratako/Magpie-Tanuki-Qwen2.5-72B-Answered) |
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- [Aratako/magpie-qwen2.5-32b-reasoning-100k-formatted](https://huggingface.co/datasets/Aratako/magpie-qwen2.5-32b-reasoning-100k-formatted) |
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- [Aratako/magpie-reasoning-llama-nemotron-70b-100k-filtered](https://huggingface.co/datasets/Aratako/magpie-reasoning-llama-nemotron-70b-100k-filtered) |
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- [Aratako/Open-Platypus-Japanese-masked-formatted](https://huggingface.co/datasets/Aratako/Open-Platypus-Japanese-masked-formatted) |
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- [kanhatakeyama/wizardlm8x22b-logical-math-coding-sft_additional-ja](https://huggingface.co/datasets/kanhatakeyama/wizardlm8x22b-logical-math-coding-sft_additional-ja) |
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- [kanhatakeyama/ramdom-to-fixed-multiturn-Calm3](https://huggingface.co/datasets/kanhatakeyama/ramdom-to-fixed-multiturn-Calm3) |
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- [Aratako/magpie-ultra-v0.1-formatted](https://huggingface.co/datasets/Aratako/magpie-ultra-v0.1-formatted) |
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- [Aratako/orca-agentinstruct-1M-v1-selected](https://huggingface.co/datasets/Aratako/orca-agentinstruct-1M-v1-selected) |
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- [Aratako/Synthetic-JP-EN-Coding-Dataset-801k-50k](https://huggingface.co/datasets/Aratako/Synthetic-JP-EN-Coding-Dataset-801k-50k) |
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## ライセンス |
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本モデルは学習に利用したデータの関係で以下のライセンスの影響を受けます。 |
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- [META LLAMA 3.1 COMMUNITY LICENSE](https://www.llama.com/llama3_1/license/)を継承します。 |
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- [Gemma Terms of Use](https://ai.google.dev/gemma/terms)を継承します。 |
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- [Qwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE)の影響を受けます。ライセンスは継承しませんが、「Built with Qwen」のような文言を記載する必要があります。 |
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## 学習に関する詳細 |
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本モデルの学習には[axolotl](https://github.com/axolotl-ai-cloud/axolotl)を使いました。パラメータ等の学習の設定は下記の自動生成された記述をご確認ください。 |
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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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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.5.2` |
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```yaml |
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base_model: google/gemma-2-27b |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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hub_model_id: Aratako/fft-1 |
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hub_strategy: "end" |
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push_dataset_to_hub: |
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hf_use_auth_token: true |
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plugins: |
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- axolotl.integrations.liger.LigerPlugin |
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liger_cross_entropy: false |
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liger_rope: true |
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liger_rms_norm: true |
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liger_swiglu: true |
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liger_fused_linear_cross_entropy: true |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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chat_template: gemma |
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datasets: |
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- path: Aratako/Magpie-Tanuki-Qwen2.5-72B-Answered |
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type: chat_template |
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field_messages: messages |
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message_field_role: role |
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message_field_content: content |
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- path: Aratako/magpie-qwen2.5-32b-reasoning-100k-formatted |
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type: chat_template |
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field_messages: conversations |
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message_field_role: role |
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message_field_content: content |
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- path: Aratako/magpie-reasoning-llama-nemotron-70b-100k-filtered |
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type: chat_template |
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field_messages: conversations |
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message_field_role: role |
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message_field_content: content |
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- path: Aratako/Open-Platypus-Japanese-masked-formatted |
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type: chat_template |
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field_messages: conversations |
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message_field_role: role |
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message_field_content: content |
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- path: kanhatakeyama/wizardlm8x22b-logical-math-coding-sft_additional-ja |
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type: chat_template |
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field_messages: messages |
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message_field_role: role |
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message_field_content: content |
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- path: kanhatakeyama/ramdom-to-fixed-multiturn-Calm3 |
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split: 20240806filtered |
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type: chat_template |
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field_messages: messages |
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message_field_role: role |
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message_field_content: content |
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- path: Aratako/magpie-ultra-v0.1-formatted |
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type: chat_template |
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field_messages: conversations |
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message_field_role: role |
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message_field_content: content |
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- path: Aratako/orca-agentinstruct-1M-v1-selected |
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type: chat_template |
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field_messages: messages |
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message_field_role: role |
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message_field_content: content |
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- path: Aratako/Synthetic-JP-EN-Coding-Dataset-801k-50k |
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type: chat_template |
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field_messages: messages |
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message_field_role: role |
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message_field_content: content |
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shuffle_merged_datasets: true |
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dataset_prepared_path: /workspace/data/fft-data |
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val_set_size: 0.003 |
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output_dir: /workspace/data/27b-fft-out-1 |
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sequence_len: 4096 |
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sample_packing: true |
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eval_sample_packing: false |
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pad_to_sequence_len: true |
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adapter: |
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lora_model_dir: |
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lora_r: |
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lora_alpha: |
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lora_dropout: |
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lora_target_linear: |
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lora_fan_in_fan_out: |
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wandb_project: 27b-fft |
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wandb_entity: aratako-lm |
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wandb_watch: |
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wandb_name: attempt-01 |
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wandb_log_model: |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 8 |
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num_epochs: 2 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: |
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cosine_min_lr_ratio: 0.1 |
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learning_rate: 0.00001 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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auto_resume_from_checkpoints: true |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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save_strategy: steps |
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save_steps: 100 |
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save_total_limit: 2 |
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warmup_steps: 10 |
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eval_steps: 100 |
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eval_batch_size: 1 |
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eval_table_size: |
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eval_max_new_tokens: |
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debug: |
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deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json |
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weight_decay: 0.01 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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pad_token: <pad> |
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``` |
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</details><br> |
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# fft-1 |
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This model is a fine-tuned version of [google/gemma-2-27b](https://huggingface.co/google/gemma-2-27b) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6122 |
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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: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 7 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 224 |
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- total_eval_batch_size: 7 |
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- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.9427 | 0.0020 | 1 | 0.9940 | |
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| 0.6566 | 0.2043 | 100 | 0.6648 | |
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| 0.6609 | 0.4086 | 200 | 0.6430 | |
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| 0.6457 | 0.6129 | 300 | 0.6306 | |
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| 0.6322 | 0.8172 | 400 | 0.6203 | |
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| 0.5082 | 1.0204 | 500 | 0.6238 | |
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| 0.5348 | 1.2247 | 600 | 0.6212 | |
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| 0.5253 | 1.4290 | 700 | 0.6181 | |
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| 0.5136 | 1.6333 | 800 | 0.6147 | |
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| 0.5125 | 1.8376 | 900 | 0.6122 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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