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Browse files- README.md +70 -0
- model-00001-of-00003.safetensors +3 -0
- model-00002-of-00003.safetensors +3 -0
- model-00003-of-00003.safetensors +3 -0
- model.safetensors.index.json +202 -0
README.md
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---
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license: mit
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base_model: microsoft/Phi-3-mini-4k-instruct
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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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- f1
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model-index:
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- name: Phi-3-mini-4k-instruct-mbti-2
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zmhzmh/huggingface/runs/0x5scv56)
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# Phi-3-mini-4k-instruct-mbti-2
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This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6372
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- Accuracy: 0.6461
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- F1: 0.7150
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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: 2e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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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: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|
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| 0.7097 | 0.1582 | 2000 | 0.6888 | 0.6080 | 0.7463 |
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| 0.6833 | 0.3164 | 4000 | 0.6675 | 0.5969 | 0.6512 |
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| 0.6713 | 0.4745 | 6000 | 0.6596 | 0.6138 | 0.6748 |
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| 0.6592 | 0.6327 | 8000 | 0.6540 | 0.6389 | 0.7222 |
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| 0.6498 | 0.7909 | 10000 | 0.6456 | 0.5914 | 0.5887 |
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| 0.6362 | 0.9491 | 12000 | 0.6372 | 0.6461 | 0.7150 |
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.3.1
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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