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README.md
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---
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license: mit
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library_name: peft
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tags:
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- trl
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- sft
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- generated_from_trainer
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base_model: microsoft/Phi-3-mini-4k-instruct
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datasets:
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- generator
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model-index:
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- name: cls_sentiment_phi3_v1
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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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# cls_sentiment_phi3_v1
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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 the generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7122
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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: 0.0002
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- train_batch_size: 2
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: constant
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- lr_scheduler_warmup_ratio: 0.03
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- num_epochs: 2
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 0.9066 | 0.2083 | 50 | 0.9011 |
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| 0.854 | 0.4167 | 100 | 0.8419 |
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| 0.787 | 0.625 | 150 | 0.8062 |
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| 0.7476 | 0.8333 | 200 | 0.7764 |
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| 0.7141 | 1.0417 | 250 | 0.7636 |
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| 0.6989 | 1.25 | 300 | 0.7528 |
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| 0.6482 | 1.4583 | 350 | 0.7397 |
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| 0.6537 | 1.6667 | 400 | 0.7207 |
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| 0.6526 | 1.875 | 450 | 0.7122 |
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### Framework versions
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- PEFT 0.11.1
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- Transformers 4.41.0
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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