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.gitattributes CHANGED
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: other
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+ base_model: Qwen/Qwen2.5-Coder-7B-Instruct
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+ tags:
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+ - llama-factory
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+ - freeze
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+ - generated_from_trainer
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+ model-index:
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+ - name: qwen_nsx_8_1
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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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+ # qwen_nsx_8_1
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+
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+ This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct) on the codes_nsx_over81 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: 5e-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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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 512
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+ - total_eval_batch_size: 32
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+ - optimizer: Use adamw_torch 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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+ - num_epochs: 1.0
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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 4.48.2
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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+ "train_steps_per_second": 0.01
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+ }
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+ {
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+ "_name_or_path": "Qwen/Qwen2.5-Coder-7B-Instruct",
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+ "architectures": [
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+ "Qwen2ForCausalLM"
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+ ],
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 151643,
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+ "hidden_act": "silu",
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+ "initializer_range": 0.02,
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+ "max_position_embeddings": 32768,
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+ "max_window_layers": 28,
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+ "model_type": "qwen2",
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+ "num_hidden_layers": 28,
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+ "num_key_value_heads": 4,
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+ "rms_norm_eps": 1e-06,
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+ "rope_scaling": {
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+ "factor": 1.0,
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+ "high_freq_factor": 4.0,
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+ "low_freq_factor": 1.0,
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+ "original_max_position_embeddings": 32768,
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+ "rope_type": "llama3"
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+ },
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.48.2",
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+ "use_cache": false,
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+ "use_sliding_window": false,
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+ "vocab_size": 152064
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+ }
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+ "top_p": 0.8,
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+ top.booster: liger_kernel
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+ top.checkpoint_path: null
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+ top.finetuning_type: freeze
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+ top.model_name: Qwen2.5-Coder-7B-Instruct
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+ top.quantization_bit: none
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+ top.quantization_method: bitsandbytes
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+ top.rope_scaling: llama3
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+ top.template: qwen
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+ train.additional_target: ''
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+ train.apollo_rank: 256
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+ train.apollo_scale: 1
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+ train.apollo_target: all
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+ train.apollo_update_interval: 200
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+ train.badam_mode: layer
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+ train.badam_switch_interval: 50
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+ train.badam_switch_mode: ascending
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+ train.badam_update_ratio: 0.05
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+ train.batch_size: 16
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+ train.compute_type: bf16
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+ train.create_new_adapter: false
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+ train.cutoff_len: 4096
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+ train.dataset:
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+ - codes_nsx_over81
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+ train.dataset_dir: data
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+ train.ds_offload: false
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+ train.ds_stage: none
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+ train.extra_args: '{}'
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+ train.freeze_extra_modules: ''
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+ train.freeze_trainable_modules: all
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+ train.galore_rank: 16
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+ train.galore_scale: 2
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+ train.galore_target: all
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+ train.galore_update_interval: 200
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+ train.gradient_accumulation_steps: 8
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+ train.learning_rate: 5e-5
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+ train.logging_steps: 1
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+ train.lora_alpha: 16
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+ train.lora_dropout: 0
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+ train.lora_rank: 8
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+ train.lora_target: ''
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+ train.loraplus_lr_ratio: 0
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+ train.lr_scheduler_type: cosine
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+ train.mask_history: false
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+ train.max_grad_norm: '1.0'
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+ train.neat_packing: true
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+ train.packing: true
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+ train.ppo_score_norm: false
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+ train.ppo_whiten_rewards: false
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+ train.pref_beta: 0.1
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+ train.pref_ftx: 0
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+ train.pref_loss: sigmoid
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+ train.report_to:
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+ - none
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+ train.resize_vocab: false
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+ train.reward_model: null
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+ train.save_steps: 500
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+ train.swanlab_api_key: ''
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+ train.swanlab_mode: cloud
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+ train.swanlab_project: llamafactory
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+ train.swanlab_run_name: ''
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+ train.train_on_prompt: false
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+ train.training_stage: Supervised Fine-Tuning
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+ train.use_apollo: true
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+ train.use_badam: false
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+ train.use_dora: false
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+ train.use_galore: false
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+ train.use_llama_pro: false
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+ train.use_pissa: false
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+ }
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+ }
running_log.txt ADDED
@@ -0,0 +1,216 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [INFO|2025-05-29 19:37:34] configuration_utils.py:696 >> loading configuration file config.json from cache at /home/kiho/.cache/huggingface/hub/models--Qwen--Qwen2.5-Coder-7B-Instruct/snapshots/c03e6d358207e414f1eca0bb1891e29f1db0e242/config.json
2
+
3
+ [INFO|2025-05-29 19:37:34] configuration_utils.py:768 >> Model config Qwen2Config {
4
+ "_name_or_path": "Qwen/Qwen2.5-Coder-7B-Instruct",
5
+ "architectures": [
6
+ "Qwen2ForCausalLM"
7
+ ],
8
+ "attention_dropout": 0.0,
9
+ "bos_token_id": 151643,
10
+ "eos_token_id": 151645,
11
+ "hidden_act": "silu",
12
+ "hidden_size": 3584,
13
+ "initializer_range": 0.02,
14
+ "intermediate_size": 18944,
15
+ "max_position_embeddings": 32768,
16
+ "max_window_layers": 28,
17
+ "model_type": "qwen2",
18
+ "num_attention_heads": 28,
19
+ "num_hidden_layers": 28,
20
+ "num_key_value_heads": 4,
21
+ "rms_norm_eps": 1e-06,
22
+ "rope_scaling": null,
23
+ "rope_theta": 1000000.0,
24
+ "sliding_window": null,
25
+ "tie_word_embeddings": false,
26
+ "torch_dtype": "bfloat16",
27
+ "transformers_version": "4.48.2",
28
+ "use_cache": true,
29
+ "use_sliding_window": false,
30
+ "vocab_size": 152064
31
+ }
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+
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+
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+ [INFO|2025-05-29 19:37:34] tokenization_utils_base.py:2034 >> loading file vocab.json from cache at /home/kiho/.cache/huggingface/hub/models--Qwen--Qwen2.5-Coder-7B-Instruct/snapshots/c03e6d358207e414f1eca0bb1891e29f1db0e242/vocab.json
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+
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+ [INFO|2025-05-29 19:37:34] tokenization_utils_base.py:2034 >> loading file merges.txt from cache at /home/kiho/.cache/huggingface/hub/models--Qwen--Qwen2.5-Coder-7B-Instruct/snapshots/c03e6d358207e414f1eca0bb1891e29f1db0e242/merges.txt
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+
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+ [INFO|2025-05-29 19:37:34] tokenization_utils_base.py:2034 >> loading file tokenizer.json from cache at /home/kiho/.cache/huggingface/hub/models--Qwen--Qwen2.5-Coder-7B-Instruct/snapshots/c03e6d358207e414f1eca0bb1891e29f1db0e242/tokenizer.json
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+
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+ [INFO|2025-05-29 19:37:34] tokenization_utils_base.py:2034 >> loading file added_tokens.json from cache at None
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+
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+ [INFO|2025-05-29 19:37:34] tokenization_utils_base.py:2034 >> loading file special_tokens_map.json from cache at None
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+
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+ [INFO|2025-05-29 19:37:34] tokenization_utils_base.py:2034 >> loading file tokenizer_config.json from cache at /home/kiho/.cache/huggingface/hub/models--Qwen--Qwen2.5-Coder-7B-Instruct/snapshots/c03e6d358207e414f1eca0bb1891e29f1db0e242/tokenizer_config.json
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+
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+ [INFO|2025-05-29 19:37:34] tokenization_utils_base.py:2034 >> loading file chat_template.jinja from cache at None
47
+
48
+ [INFO|2025-05-29 19:37:34] tokenization_utils_base.py:2304 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
49
+
50
+ [INFO|2025-05-29 19:37:34] logging.py:157 >> Add <|im_end|> to stop words.
51
+
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+ [INFO|2025-05-29 19:37:34] logging.py:157 >> Loading dataset Codes_query_filtered_330k_ns_over8_1.json...
53
+
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+ [INFO|2025-05-29 19:37:47] configuration_utils.py:696 >> loading configuration file config.json from cache at /home/kiho/.cache/huggingface/hub/models--Qwen--Qwen2.5-Coder-7B-Instruct/snapshots/c03e6d358207e414f1eca0bb1891e29f1db0e242/config.json
55
+
56
+ [INFO|2025-05-29 19:37:47] configuration_utils.py:768 >> Model config Qwen2Config {
57
+ "_name_or_path": "Qwen/Qwen2.5-Coder-7B-Instruct",
58
+ "architectures": [
59
+ "Qwen2ForCausalLM"
60
+ ],
61
+ "attention_dropout": 0.0,
62
+ "bos_token_id": 151643,
63
+ "eos_token_id": 151645,
64
+ "hidden_act": "silu",
65
+ "hidden_size": 3584,
66
+ "initializer_range": 0.02,
67
+ "intermediate_size": 18944,
68
+ "max_position_embeddings": 32768,
69
+ "max_window_layers": 28,
70
+ "model_type": "qwen2",
71
+ "num_attention_heads": 28,
72
+ "num_hidden_layers": 28,
73
+ "num_key_value_heads": 4,
74
+ "rms_norm_eps": 1e-06,
75
+ "rope_scaling": null,
76
+ "rope_theta": 1000000.0,
77
+ "sliding_window": null,
78
+ "tie_word_embeddings": false,
79
+ "torch_dtype": "bfloat16",
80
+ "transformers_version": "4.48.2",
81
+ "use_cache": true,
82
+ "use_sliding_window": false,
83
+ "vocab_size": 152064
84
+ }
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+
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+
87
+ [WARNING|2025-05-29 19:37:47] logging.py:162 >> Input length is smaller than max length. Consider increase input length.
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+
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+ [INFO|2025-05-29 19:37:47] logging.py:157 >> Using llama3 scaling strategy and setting scaling factor to 1.0.
90
+
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+ [INFO|2025-05-29 19:37:47] logging.py:157 >> Using block diagonal attention for sequence packing without cross-attention.
92
+
93
+ [INFO|2025-05-29 19:37:47] logging.py:157 >> Liger kernel has been applied to the model.
94
+
95
+ [INFO|2025-05-29 19:37:47] modeling_utils.py:3904 >> loading weights file model.safetensors from cache at /home/kiho/.cache/huggingface/hub/models--Qwen--Qwen2.5-Coder-7B-Instruct/snapshots/c03e6d358207e414f1eca0bb1891e29f1db0e242/model.safetensors.index.json
96
+
97
+ [INFO|2025-05-29 19:37:47] modeling_utils.py:1582 >> Instantiating Qwen2ForCausalLM model under default dtype torch.bfloat16.
98
+
99
+ [INFO|2025-05-29 19:37:47] configuration_utils.py:1140 >> Generate config GenerationConfig {
100
+ "bos_token_id": 151643,
101
+ "eos_token_id": 151645
102
+ }
103
+
104
+
105
+ [INFO|2025-05-29 19:37:57] modeling_utils.py:4888 >> All model checkpoint weights were used when initializing Qwen2ForCausalLM.
106
+
107
+
108
+ [INFO|2025-05-29 19:37:57] modeling_utils.py:4896 >> All the weights of Qwen2ForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-Coder-7B-Instruct.
109
+ If your task is similar to the task the model of the checkpoint was trained on, you can already use Qwen2ForCausalLM for predictions without further training.
110
+
111
+ [INFO|2025-05-29 19:37:57] configuration_utils.py:1095 >> loading configuration file generation_config.json from cache at /home/kiho/.cache/huggingface/hub/models--Qwen--Qwen2.5-Coder-7B-Instruct/snapshots/c03e6d358207e414f1eca0bb1891e29f1db0e242/generation_config.json
112
+
113
+ [INFO|2025-05-29 19:37:57] configuration_utils.py:1140 >> Generate config GenerationConfig {
114
+ "bos_token_id": 151643,
115
+ "do_sample": true,
116
+ "eos_token_id": [
117
+ 151645,
118
+ 151643
119
+ ],
120
+ "pad_token_id": 151643,
121
+ "repetition_penalty": 1.1,
122
+ "temperature": 0.7,
123
+ "top_k": 20,
124
+ "top_p": 0.8
125
+ }
126
+
127
+
128
+ [INFO|2025-05-29 19:37:57] logging.py:157 >> Gradient checkpointing enabled.
129
+
130
+ [INFO|2025-05-29 19:37:57] logging.py:157 >> Using torch SDPA for faster training and inference.
131
+
132
+ [INFO|2025-05-29 19:37:57] logging.py:157 >> Upcasting trainable params to float32.
133
+
134
+ [INFO|2025-05-29 19:37:57] logging.py:157 >> Fine-tuning method: Freeze
135
+
136
+ [INFO|2025-05-29 19:37:57] logging.py:157 >> Set trainable layers: .26.,.27.
137
+
138
+ [INFO|2025-05-29 19:37:57] logging.py:157 >> trainable params: 466,115,584 || all params: 7,615,616,512 || trainable%: 6.1205
139
+
140
+ [INFO|2025-05-29 19:37:57] trainer.py:741 >> Using auto half precision backend
141
+
142
+ [INFO|2025-05-29 19:37:57] logging.py:157 >> Found linear modules: k_proj,q_proj,o_proj,down_proj,v_proj,gate_proj,up_proj
143
+
144
+ [INFO|2025-05-29 19:37:57] logging.py:157 >> Using APOLLO optimizer with args: {'rank': 256, 'proj': 'random', 'proj_type': 'std', 'update_proj_gap': 200, 'scale': 1, 'scale_type': 'channel', 'scale_front': False}.
145
+
146
+ [INFO|2025-05-29 19:37:57] trainer.py:2369 >> ***** Running training *****
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+
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+ [INFO|2025-05-29 19:37:57] trainer.py:2370 >> Num examples = 4,739
149
+
150
+ [INFO|2025-05-29 19:37:57] trainer.py:2371 >> Num Epochs = 1
151
+
152
+ [INFO|2025-05-29 19:37:57] trainer.py:2372 >> Instantaneous batch size per device = 16
153
+
154
+ [INFO|2025-05-29 19:37:57] trainer.py:2375 >> Total train batch size (w. parallel, distributed & accumulation) = 512
155
+
156
+ [INFO|2025-05-29 19:37:57] trainer.py:2376 >> Gradient Accumulation steps = 8
157
+
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+ [INFO|2025-05-29 19:37:57] trainer.py:2377 >> Total optimization steps = 9
159
+
160
+ [INFO|2025-05-29 19:37:57] trainer.py:2378 >> Number of trainable parameters = 466,115,584
161
+
162
+ [INFO|2025-05-29 19:39:46] logging.py:157 >> {'loss': 0.8250, 'learning_rate': 4.8492e-05, 'epoch': 0.11, 'throughput': 19409.05}
163
+
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+ [INFO|2025-05-29 19:41:28] logging.py:157 >> {'loss': 0.7867, 'learning_rate': 4.4151e-05, 'epoch': 0.21, 'throughput': 20051.40}
165
+
166
+ [INFO|2025-05-29 19:43:10] logging.py:157 >> {'loss': 0.7849, 'learning_rate': 3.7500e-05, 'epoch': 0.32, 'throughput': 20211.57}
167
+
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+ [INFO|2025-05-29 19:44:51] logging.py:157 >> {'loss': 0.7609, 'learning_rate': 2.9341e-05, 'epoch': 0.43, 'throughput': 20309.39}
169
+
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+ [INFO|2025-05-29 19:46:33] logging.py:157 >> {'loss': 0.7475, 'learning_rate': 2.0659e-05, 'epoch': 0.53, 'throughput': 20377.09}
171
+
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+ [INFO|2025-05-29 19:48:15] logging.py:157 >> {'loss': 0.7783, 'learning_rate': 1.2500e-05, 'epoch': 0.64, 'throughput': 20417.33}
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+
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+ [INFO|2025-05-29 19:49:56] logging.py:157 >> {'loss': 0.7453, 'learning_rate': 5.8489e-06, 'epoch': 0.75, 'throughput': 20443.35}
175
+
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+ [INFO|2025-05-29 19:51:38] logging.py:157 >> {'loss': 0.7393, 'learning_rate': 1.5077e-06, 'epoch': 0.85, 'throughput': 20461.76}
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+
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+ [INFO|2025-05-29 19:53:20] logging.py:157 >> {'loss': 0.7599, 'learning_rate': 0.0000e+00, 'epoch': 0.96, 'throughput': 20477.77}
179
+
180
+ [INFO|2025-05-29 19:53:20] trainer.py:3910 >> Saving model checkpoint to saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1/checkpoint-9
181
+
182
+ [INFO|2025-05-29 19:53:20] configuration_utils.py:420 >> Configuration saved in saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1/checkpoint-9/config.json
183
+
184
+ [INFO|2025-05-29 19:53:20] configuration_utils.py:909 >> Configuration saved in saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1/checkpoint-9/generation_config.json
185
+
186
+ [INFO|2025-05-29 19:53:43] modeling_utils.py:2996 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 4 checkpoint shards. You can find where each parameters has been saved in the index located at saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1/checkpoint-9/model.safetensors.index.json.
187
+
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+ [INFO|2025-05-29 19:53:43] tokenization_utils_base.py:2491 >> tokenizer config file saved in saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1/checkpoint-9/tokenizer_config.json
189
+
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+ [INFO|2025-05-29 19:53:43] tokenization_utils_base.py:2500 >> Special tokens file saved in saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1/checkpoint-9/special_tokens_map.json
191
+
192
+ [INFO|2025-05-29 19:53:43] trainer.py:2643 >>
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+
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+ Training completed. Do not forget to share your model on huggingface.co/models =)
195
+
196
+
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+
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+ [INFO|2025-05-29 19:53:43] trainer.py:3910 >> Saving model checkpoint to saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1
199
+
200
+ [INFO|2025-05-29 19:53:43] configuration_utils.py:420 >> Configuration saved in saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1/config.json
201
+
202
+ [INFO|2025-05-29 19:53:43] configuration_utils.py:909 >> Configuration saved in saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1/generation_config.json
203
+
204
+ [INFO|2025-05-29 19:54:07] modeling_utils.py:2996 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 4 checkpoint shards. You can find where each parameters has been saved in the index located at saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1/model.safetensors.index.json.
205
+
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+ [INFO|2025-05-29 19:54:07] tokenization_utils_base.py:2491 >> tokenizer config file saved in saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1/tokenizer_config.json
207
+
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+ [INFO|2025-05-29 19:54:07] tokenization_utils_base.py:2500 >> Special tokens file saved in saves/Qwen2.5-Coder-7B-Instruct/freeze/qwen_nsx_8_1/special_tokens_map.json
209
+
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+ [WARNING|2025-05-29 19:54:07] logging.py:162 >> No metric eval_loss to plot.
211
+
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+ [WARNING|2025-05-29 19:54:07] logging.py:162 >> No metric eval_accuracy to plot.
213
+
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+ [INFO|2025-05-29 19:54:07] modelcard.py:449 >> Dropping the following result as it does not have all the necessary fields:
215
+ {'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}}
216
+
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+ "single_word": false
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+ }
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