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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,69 @@
+---
+library_name: transformers
+license: other
+base_model: Qwen/Qwen2.5-Math-1.5B
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: MATH_training_Qwen_QwQ_32B_Preview
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# MATH_training_Qwen_QwQ_32B_Preview
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-Math-1.5B](https://huggingface.co/Qwen/Qwen2.5-Math-1.5B) on the MATH_training_Qwen_QwQ_32B_Preview dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3077
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 2
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 8
+- total_eval_batch_size: 4
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.2929        | 0.2999 | 200  | 0.3342          |
+| 0.293         | 0.5997 | 400  | 0.3171          |
+| 0.3495        | 0.8996 | 600  | 0.3088          |
+| 0.2929        | 1.1994 | 800  | 0.3114          |
+| 0.2238        | 1.4993 | 1000 | 0.3090          |
+| 0.1791        | 1.7991 | 1200 | 0.3081          |
+
+
+### Framework versions
+
+- Transformers 4.46.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.3

added_tokens.json

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all_results.json

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+    "epoch": 2.0,
+    "eval_loss": 0.3077423870563507,
+    "eval_runtime": 2.3409,
+    "eval_samples_per_second": 23.068,
+    "eval_steps_per_second": 5.981,
+    "total_flos": 17118166450176.0,
+    "train_loss": 0.28788902377081416,
+    "train_runtime": 1140.6121,
+    "train_samples_per_second": 9.344,
+    "train_steps_per_second": 1.17
+}

config.json

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+{
+  "_name_or_path": "Qwen/Qwen2.5-Math-1.5B",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
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+  "hidden_act": "silu",
+  "hidden_size": 1536,
+  "initializer_range": 0.02,
+  "intermediate_size": 8960,
+  "max_position_embeddings": 4096,
+  "max_window_layers": 21,
+  "model_type": "qwen2",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 2,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 10000,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.46.1",
+  "use_cache": false,
+  "use_mrope": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

eval_results.json

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+    "eval_loss": 0.3077423870563507,
+    "eval_runtime": 2.3409,
+    "eval_samples_per_second": 23.068,
+    "eval_steps_per_second": 5.981
+}

generation_config.json

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+}

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special_tokens_map.json

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tokenizer_config.json

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train_results.json

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+}

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