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--- |
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license: mit |
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base_model: microsoft/phi-2 |
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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: phi_2_twitter |
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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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# phi_2_twitter |
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5104 |
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- Accuracy: 0.7647 |
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- F1 Macro: 0.7172 |
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- F1 Micro: 0.7647 |
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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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| 0.5921 | 0.18 | 50 | 0.6037 | 0.6958 | 0.5054 | 0.6958 | |
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| 0.5904 | 0.37 | 100 | 0.5537 | 0.7188 | 0.6277 | 0.7188 | |
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| 0.5021 | 0.55 | 150 | 0.6041 | 0.7160 | 0.5774 | 0.7160 | |
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| 0.5266 | 0.74 | 200 | 0.5544 | 0.7096 | 0.6496 | 0.7096 | |
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| 0.5427 | 0.92 | 250 | 0.5331 | 0.7399 | 0.6915 | 0.7399 | |
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| 0.4715 | 1.1 | 300 | 0.5436 | 0.7399 | 0.6361 | 0.7399 | |
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| 0.4829 | 1.29 | 350 | 0.5217 | 0.7564 | 0.7135 | 0.7564 | |
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| 0.4676 | 1.47 | 400 | 0.5225 | 0.7537 | 0.6829 | 0.7537 | |
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| 0.5196 | 1.65 | 450 | 0.5163 | 0.7629 | 0.7096 | 0.7629 | |
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| 0.4815 | 1.84 | 500 | 0.5213 | 0.7656 | 0.7215 | 0.7656 | |
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| 0.4836 | 2.02 | 550 | 0.5221 | 0.7619 | 0.7191 | 0.7619 | |
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| 0.4945 | 2.21 | 600 | 0.5134 | 0.7638 | 0.7173 | 0.7638 | |
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| 0.4103 | 2.39 | 650 | 0.5125 | 0.7684 | 0.7211 | 0.7684 | |
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| 0.4191 | 2.57 | 700 | 0.5108 | 0.7684 | 0.7226 | 0.7684 | |
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| 0.5004 | 2.76 | 750 | 0.5104 | 0.7647 | 0.7172 | 0.7647 | |
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| 0.4398 | 2.94 | 800 | 0.5114 | 0.7675 | 0.7138 | 0.7675 | |
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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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