End of training
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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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model-index:
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- name: phi-3-vi-sft-1
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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-3-vi-sft-1
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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 None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0711
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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: 8
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- eval_batch_size: 4
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- seed: 3407
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- gradient_accumulation_steps: 4
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- total_train_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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- lr_scheduler_warmup_steps: 5
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- num_epochs: 1
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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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| 1.4031 | 0.17 | 40 | 1.2004 |
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| 1.1508 | 0.34 | 80 | 1.1312 |
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| 1.1055 | 0.51 | 120 | 1.1002 |
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| 1.0814 | 0.67 | 160 | 1.0820 |
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| 1.0735 | 0.84 | 200 | 1.0711 |
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.39.3
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- Pytorch 2.1.2
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- Datasets 2.16.0
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- Tokenizers 0.15.2
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runs/Apr26_17-04-54_05a7b4b1699b/events.out.tfevents.1714151097.05a7b4b1699b.24.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:0d0aa0a849fdf8fb9813323d34d83c8784fafc36b7fd80ea9d8c29096fe150f0
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size 8174
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