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Model: lllqaq/Qwen2.5-Coder-14B-Instruct-num11_v1-v2-v3-pairs-v3-triples-rope1mfix
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: other
+base_model: Qwen/Qwen2.5-Coder-14B-Instruct
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: Qwen2.5-Coder-14B-Instruct-num11
+  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. -->
+
+# Qwen2.5-Coder-14B-Instruct-num11
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-14B-Instruct) on the fim_midtrain_v1, the fim_midtrain_v2, the fim_midtrain_v3_multi_pairs, the fim_midtrain_v3_multi_pairs_0317, the fim_midtrain_v3_multi_triples and the fim_midtrain_v3_multi_triples_0317 datasets.
+
+## RoPE config fix
+
+This upload keeps the original weights and adds top-level `"rope_theta": 1000000.0` to `config.json` so Qwen2 loaders in current Transformers/vLLM versions do not fall back to the default `10000.0` RoPE base.
+
+## 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: 1
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- total_eval_batch_size: 64
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 0.1
+- num_epochs: 1.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.6.0+cu124
+- Datasets 4.0.0
+- Tokenizers 0.22.2