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--- |
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license: other |
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base_model: Qwen/Qwen1.5-1.8B |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: Qwen1.5_1.8B_scotus |
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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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# Qwen1.5_1.8B_scotus |
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This model is a fine-tuned version of [Qwen/Qwen1.5-1.8B](https://huggingface.co/Qwen/Qwen1.5-1.8B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6403 |
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- Accuracy: 0.515 |
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- F1 Macro: 0.3569 |
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- F1 Micro: 0.515 |
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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: 5e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:| |
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| 2.1746 | 0.32 | 50 | 2.2792 | 0.2693 | 0.1148 | 0.2693 | |
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| 1.5758 | 0.64 | 100 | 1.9309 | 0.41 | 0.2291 | 0.41 | |
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| 1.7312 | 0.96 | 150 | 1.7475 | 0.4714 | 0.2547 | 0.4714 | |
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| 1.2859 | 1.27 | 200 | 1.7939 | 0.4686 | 0.3019 | 0.4686 | |
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| 1.1971 | 1.59 | 250 | 1.7146 | 0.4957 | 0.3307 | 0.4957 | |
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| 1.1271 | 1.91 | 300 | 1.6403 | 0.515 | 0.3569 | 0.515 | |
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| 0.8436 | 2.23 | 350 | 1.7995 | 0.51 | 0.3717 | 0.51 | |
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| 0.7723 | 2.55 | 400 | 1.8401 | 0.5029 | 0.3723 | 0.5029 | |
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| 0.7211 | 2.87 | 450 | 1.8232 | 0.5179 | 0.3753 | 0.5179 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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