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--- |
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license: mit |
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base_model: microsoft/Phi-3-small-8k-instruct |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: phi3-spin-Llama2-data |
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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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# phi3-spin-Llama2-data |
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This model is a fine-tuned version of [microsoft/Phi-3-small-8k-instruct](https://huggingface.co/microsoft/Phi-3-small-8k-instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0005 |
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- Rewards/real: 0.7586 |
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- Rewards/generated: -92.4366 |
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- Rewards/accuracies: 1.0 |
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- Rewards/margins: 93.1952 |
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- Logps/generated: -1271.4552 |
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- Logps/real: -248.8362 |
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- Logits/generated: -inf |
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- Logits/real: -inf |
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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-07 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/real | Rewards/generated | Rewards/accuracies | Rewards/margins | Logps/generated | Logps/real | Logits/generated | Logits/real | |
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|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------------:|:------------------:|:---------------:|:---------------:|:----------:|:----------------:|:-----------:| |
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| 0.0901 | 0.29 | 500 | 0.0191 | -0.2438 | -52.9080 | 0.9922 | 52.6642 | -876.1692 | -258.8595 | -inf | -inf | |
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| 0.0024 | 0.58 | 1000 | 0.0014 | 1.6797 | -78.7354 | 1.0 | 80.4151 | -1134.4436 | -239.6249 | -inf | -inf | |
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| 0.0926 | 0.87 | 1500 | 0.0005 | 0.7586 | -92.4366 | 1.0 | 93.1952 | -1271.4552 | -248.8362 | -inf | -inf | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.2 |
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