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gpt-oss-120b-multilingual-reasoning

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gpt_oss
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  1. README.md +135 -0
  2. config.json +1 -1
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: axolotl-ai-co/gpt-oss-120b-dequantized
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - HuggingFaceH4/Multilingual-Thinking
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+ model-index:
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+ - name: outputs/gpt-oss-120b/
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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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+ [<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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+
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+ axolotl version: `0.12.0`
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+ ```yaml
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+ # the original mxfp4 quantized model is not supported with FSDP cpu_ram_efficient_loading
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+ # FSDP cpu_ram_efficient_loading is used to reduce the initial CPU memory usage when loading the model
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+ base_model: axolotl-ai-co/gpt-oss-120b-dequantized
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+
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+ use_kernels: false
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+
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+ dp_shard_size: 8 # requires 2x8xH100 nodes
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+
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+ plugins:
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+ - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
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+
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+ experimental_skip_move_to_device: true # prevent OOM by NOT putting model to GPU before sharding
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+
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+ datasets:
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+ - path: HuggingFaceH4/Multilingual-Thinking
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+ type: chat_template
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+ field_thinking: thinking
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+ template_thinking_key: thinking
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+
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+ dataset_prepared_path: last_run_prepared
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+ val_set_size: 0
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+ output_dir: ./outputs/gpt-oss-120b/
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+ #save_only_model: true
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+
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+ sequence_len: 4096
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+ sample_packing: true
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+ pad_to_sequence_len: true
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+
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+ wandb_project: gpt-oss-20b
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+ wandb_name: fft-20b
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+
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+ gradient_accumulation_steps: 1
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+ micro_batch_size: 4
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+ num_epochs: 1
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+
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+ optimizer: adamw_torch_fused # 8bit optimizers do not work with FSDP2 offload
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+ lr_scheduler: constant_with_warmup
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+ learning_rate: 2e-5
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+ load_best_model_at_end: false
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+
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+ bf16: true
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+ tf32: true
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+
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+ flash_attention: true
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+ attn_implementation: kernels-community/vllm-flash-attn3
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+
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+ gradient_checkpointing: true
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+ activation_offloading: true
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+
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+ logging_steps: 1
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+ saves_per_epoch: 1
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+
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+ warmup_ratio: 0.03
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+
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+ special_tokens:
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+ eot_tokens:
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+ - "<|end|>"
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+
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+ #deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
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+ fsdp_version: 2
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+ fsdp_config:
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+ offload_params: true
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+ state_dict_type: SHARDED_STATE_DICT
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+ auto_wrap_policy: TRANSFORMER_BASED_WRAP
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+ transformer_layer_cls_to_wrap: GptOssDecoderLayer
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+ reshard_after_forward: true
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+ cpu_ram_efficient_loading: true
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+ ```
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+
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+ </details><br>
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+
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+ # outputs/gpt-oss-120b/
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+
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+ This model is a fine-tuned version of [axolotl-ai-co/gpt-oss-120b-dequantized](https://huggingface.co/axolotl-ai-co/gpt-oss-120b-dequantized) on the HuggingFaceH4/Multilingual-Thinking dataset.
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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: 2e-05
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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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+ - distributed_type: multi-GPU
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+ - num_devices: 8
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+ - total_train_batch_size: 32
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+ - total_eval_batch_size: 32
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: constant_with_warmup
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+ - training_steps: 8
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.55.0
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+ - Pytorch 2.8.0+cu128
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+ - Datasets 4.0.0
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+ - Tokenizers 0.21.4
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  "attention_dropout": 0.0,
 
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  "architectures": [
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  "attention_bias": true,
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  "attention_dropout": 0.0,
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