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README.md
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library_name: transformers
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license: other
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base_model: Qwen/Qwen2.5-0.5B-Instruct
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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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---
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library_name: transformers
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license: other
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base_model: Qwen/Qwen2.5-0.5B-Instruct
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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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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: reranker_binary_filt_train
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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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# reranker_binary_filt_train
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This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) on the reranker_binary_filt_train dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0526
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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: 1e-05
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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: 8
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- total_train_batch_size: 8
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- total_eval_batch_size: 8
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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: 0.01
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- num_epochs: 1.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:-----:|:---------------:|
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| 0.0517 | 0.1000 | 1937 | 0.0871 |
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| 0.114 | 0.2001 | 3874 | 0.0835 |
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| 0.1033 | 0.3001 | 5811 | 0.0735 |
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| 0.0544 | 0.4001 | 7748 | 0.0663 |
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| 0.1169 | 0.5001 | 9685 | 0.0623 |
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| 0.05 | 0.6002 | 11622 | 0.0599 |
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| 0.0951 | 0.7002 | 13559 | 0.0566 |
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| 0.0497 | 0.8002 | 15496 | 0.0551 |
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| 0.1002 | 0.9002 | 17433 | 0.0532 |
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### Framework versions
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- Transformers 4.46.1
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- Pytorch 2.4.0+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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