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Model: guangyangnlp/Qwen3-1.7B-SFT-medical-2e-5 Source: Original Platform
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README.md
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README.md
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---
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library_name: transformers
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license: other
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base_model: Qwen/Qwen3-1.7B
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tags:
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- llama-factory
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- full
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- generated_from_trainer
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model-index:
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- name: medical-o1-sft-full
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results: []
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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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# medical-o1-sft-full
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This model is a fine-tuned version of [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B) on the medical_o1_train dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4089
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 128
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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: cosine
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- lr_scheduler_warmup_steps: 0.05
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- num_epochs: 3.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.4962 | 0.3419 | 50 | 1.4686 |
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| 1.4215 | 0.6838 | 100 | 1.4337 |
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| 1.3304 | 1.0205 | 150 | 1.4194 |
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| 1.3097 | 1.3624 | 200 | 1.4159 |
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| 1.3175 | 1.7043 | 250 | 1.4089 |
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| 1.2195 | 2.0410 | 300 | 1.4176 |
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| 1.2726 | 2.3829 | 350 | 1.4229 |
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| 1.1895 | 2.7248 | 400 | 1.4216 |
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### Framework versions
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- Transformers 5.0.0
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- Pytorch 2.10.0+cu128
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- Datasets 4.0.0
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- Tokenizers 0.22.2
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all_results.json
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all_results.json
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{
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"epoch": 3.0,
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"eval_loss": 1.4088929891586304,
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"eval_runtime": 13.9279,
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"eval_samples_per_second": 70.793,
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"eval_steps_per_second": 8.903,
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"total_flos": 5.3379040973665075e+17,
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"train_loss": 1.3470534840408637,
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"train_runtime": 3006.8003,
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"train_samples_per_second": 18.676,
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"train_steps_per_second": 0.147
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}
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config.json
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config.json
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{
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"architectures": [
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"Qwen3ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": null,
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"dtype": "float32",
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"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 6144,
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"layer_types": [
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention"
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],
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"max_position_embeddings": 40960,
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"max_window_layers": 28,
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"model_type": "qwen3",
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"num_attention_heads": 16,
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"num_hidden_layers": 28,
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"num_key_value_heads": 8,
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"pad_token_id": 151643,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_theta": 1000000,
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"rope_type": "default"
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"sliding_window": null,
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"tie_word_embeddings": true,
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"transformers_version": "5.0.0",
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"use_cache": false,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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eval_results.json
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eval_results.json
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{
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"epoch": 3.0,
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"eval_loss": 1.4088929891586304,
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"eval_runtime": 13.9279,
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"eval_samples_per_second": 70.793,
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"eval_steps_per_second": 8.903
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}
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generation_config.json
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generation_config.json
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{
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"do_sample": true,
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"temperature": 0.6,
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"top_k": 20,
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"top_p": 0.95,
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"transformers_version": "5.0.0"
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}
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model.safetensors
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model.safetensors
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tokenizer.json
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tokenizer.json
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tokenizer_config.json
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tokenizer_config.json
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"add_prefix_space": false,
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"<|video_pad|>"
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"is_local": false,
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"model_max_length": 131072,
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"pad_token": "<|endoftext|>",
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"padding_side": "right",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"unk_token": null
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}
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train_results.json
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train_results.json
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{
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"epoch": 3.0,
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trainer_state.json
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trainer_state.json
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