sanjeev-bhandari01
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End of training
Browse files- README.md +65 -0
- generation_config.json +11 -0
README.md
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---
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license: mit
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base_model: microsoft/Phi-3-mini-128k-instruct
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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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datasets:
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- generator
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model-index:
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- name: phi-3-small-sft-lora
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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-small-sft-lora
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This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2964
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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: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 128
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- training_steps: 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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| 0.6299 | 1.0 | 1 | 1.2966 |
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| 0.6065 | 1.9692 | 2 | 1.2964 |
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### Framework versions
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- Transformers 4.41.0
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": [
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32000,
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32001,
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32007
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],
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"pad_token_id": 32000,
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"transformers_version": "4.41.0"
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}
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