Hugging Face's logo

ondevicellm
/
phi-1_5_sft

Text Generation
Transformers
TensorBoard
Safetensors
phi
alignment-handbook
trl
sft
Generated from Trainer
conversational
custom_code
text-generation-inference
Model card Files
xet
Metrics Community
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Files changed (8) hide show
  1. README.md +95 -0
  2. all_results.json +13 -0
  3. eval_results.json +8 -0
  4. generation_config.json +4 -0
  5. runs/Feb27_20-52-50_main1/events.out.tfevents.1709068444.main1.69011.0 +2 -2
  6. runs/Feb27_20-52-50_main1/events.out.tfevents.1709087925.main1.69011.1 +3 -0
  7. train_results.json +8 -0
  8. trainer_state.json +3862 -0
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+ ---
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+ license: mit
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+ base_model: microsoft/phi-1_5
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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-1_5_sft
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+ results: []
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+ ---
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+
15
+ <!-- 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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+
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+ # phi-1_5_sft
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+
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+ This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the generator dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2542
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 16
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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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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 128
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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: cosine
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+ - lr_scheduler_warmup_steps: 120
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.3099 | 0.1 | 100 | 1.3398 |
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+ | 1.3131 | 0.2 | 200 | 1.3159 |
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+ | 1.3009 | 0.3 | 300 | 1.3046 |
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+ | 1.2915 | 0.4 | 400 | 1.2967 |
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+ | 1.2714 | 0.5 | 500 | 1.2906 |
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+ | 1.2811 | 0.6 | 600 | 1.2854 |
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+ | 1.2621 | 0.7 | 700 | 1.2807 |
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+ | 1.2406 | 0.8 | 800 | 1.2767 |
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+ | 1.2371 | 0.9 | 900 | 1.2731 |
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+ | 1.2547 | 1.0 | 1000 | 1.2699 |
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+ | 1.2085 | 1.1 | 1100 | 1.2693 |
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+ | 1.2253 | 1.2 | 1200 | 1.2669 |
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+ | 1.215 | 1.3 | 1300 | 1.2649 |
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+ | 1.2103 | 1.4 | 1400 | 1.2630 |
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+ | 1.2081 | 1.5 | 1500 | 1.2612 |
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+ | 1.2033 | 1.6 | 1600 | 1.2597 |
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+ | 1.2307 | 1.7 | 1700 | 1.2582 |
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+ | 1.2038 | 1.8 | 1800 | 1.2568 |
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+ | 1.2014 | 1.9 | 1900 | 1.2557 |
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+ | 1.188 | 2.0 | 2000 | 1.2546 |
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+ | 1.1473 | 2.1 | 2100 | 1.2563 |
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+ | 1.1872 | 2.2 | 2200 | 1.2559 |
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+ | 1.2086 | 2.3 | 2300 | 1.2553 |
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+ | 1.1896 | 2.4 | 2400 | 1.2550 |
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+ | 1.1733 | 2.5 | 2500 | 1.2548 |
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+ | 1.1665 | 2.6 | 2600 | 1.2544 |
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+ | 1.1499 | 2.7 | 2700 | 1.2543 |
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+ | 1.1779 | 2.8 | 2800 | 1.2542 |
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+ | 1.1746 | 2.9 | 2900 | 1.2542 |
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+
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+
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+ ### Framework versions
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+ - Transformers 4.37.0
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+ - Pytorch 2.1.2+cu118
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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