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Qwen2.5-14B-Instruct_Long_CoT_lora

PEFT
Safetensors
llama-factory
lora
Generated from Trainer
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1
lbourdois commited on
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1 Parent(s): ea555b9

Improve language tag

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Hi! As the model is multilingual, this is a PR to add other languages than English to the language tag to improve the referencing. Note that 29 languages are announced in the README, but only 13 are explicitly listed. I was therefore only able to add these 13 languages.

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  1. README.md +91 -77
README.md CHANGED
@@ -1,78 +1,92 @@
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- ---
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- library_name: peft
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- license: other
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- base_model: Qwen/Qwen2.5-14B-Instruct
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- tags:
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- - llama-factory
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- - lora
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- - generated_from_trainer
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- model-index:
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- - name: MATH_training_response_QwQ_32B_Preview
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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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- # MATH_training_response_QwQ_32B_Preview
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-
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- This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) on the MATH_training_Qwen_QwQ_32B_Preview dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 0.2534
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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: 0.0001
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- - train_batch_size: 1
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- - eval_batch_size: 1
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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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- - total_train_batch_size: 4
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- - total_eval_batch_size: 4
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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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- - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 2.0
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-
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:------:|:----:|:---------------:|
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- | 0.3648 | 0.1500 | 200 | 0.3127 |
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- | 0.2407 | 0.3001 | 400 | 0.2855 |
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- | 0.2113 | 0.4501 | 600 | 0.2747 |
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- | 0.2523 | 0.6002 | 800 | 0.2683 |
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- | 0.2713 | 0.7502 | 1000 | 0.2642 |
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- | 0.2373 | 0.9002 | 1200 | 0.2599 |
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- | 0.1968 | 1.0503 | 1400 | 0.2605 |
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- | 0.2904 | 1.2003 | 1600 | 0.2587 |
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- | 0.1625 | 1.3503 | 1800 | 0.2572 |
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- | 0.2277 | 1.5004 | 2000 | 0.2559 |
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- | 0.2696 | 1.6504 | 2200 | 0.2538 |
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- | 0.2377 | 1.8005 | 2400 | 0.2540 |
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- | 0.1775 | 1.9505 | 2600 | 0.2534 |
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-
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-
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- ### Framework versions
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-
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- - PEFT 0.12.0
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- - Transformers 4.46.1
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- - Pytorch 2.5.1+cu124
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- - Datasets 3.1.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - Tokenizers 0.20.3
 
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+ ---
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+ library_name: peft
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+ license: other
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+ base_model: Qwen/Qwen2.5-14B-Instruct
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+ tags:
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+ - llama-factory
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+ - lora
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+ - generated_from_trainer
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+ language:
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+ - zho
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+ - eng
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+ - fra
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+ - spa
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+ - por
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+ - deu
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+ - ita
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+ - rus
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+ - jpn
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+ - kor
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+ - vie
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+ - tha
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+ - ara
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+ model-index:
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+ - name: MATH_training_response_QwQ_32B_Preview
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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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+ # MATH_training_response_QwQ_32B_Preview
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+
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+ This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) on the MATH_training_Qwen_QwQ_32B_Preview dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2534
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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
42
+
43
+ More information needed
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+
45
+ ## Training and evaluation data
46
+
47
+ More information needed
48
+
49
+ ## Training procedure
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+
51
+ ### Training hyperparameters
52
+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
57
+ - seed: 42
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+ - distributed_type: multi-GPU
59
+ - num_devices: 4
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+ - total_train_batch_size: 4
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+ - total_eval_batch_size: 4
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 2.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 0.3648 | 0.1500 | 200 | 0.3127 |
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+ | 0.2407 | 0.3001 | 400 | 0.2855 |
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+ | 0.2113 | 0.4501 | 600 | 0.2747 |
74
+ | 0.2523 | 0.6002 | 800 | 0.2683 |
75
+ | 0.2713 | 0.7502 | 1000 | 0.2642 |
76
+ | 0.2373 | 0.9002 | 1200 | 0.2599 |
77
+ | 0.1968 | 1.0503 | 1400 | 0.2605 |
78
+ | 0.2904 | 1.2003 | 1600 | 0.2587 |
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+ | 0.1625 | 1.3503 | 1800 | 0.2572 |
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+ | 0.2277 | 1.5004 | 2000 | 0.2559 |
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+ | 0.2696 | 1.6504 | 2200 | 0.2538 |
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+ | 0.2377 | 1.8005 | 2400 | 0.2540 |
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+ | 0.1775 | 1.9505 | 2600 | 0.2534 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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+ - Transformers 4.46.1
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.1.0
92
  - Tokenizers 0.20.3