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--- |
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library_name: peft |
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license: mit |
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base_model: microsoft/phi-2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: phi2-mentalchat16k |
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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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# phi2-mentalchat16k |
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7112 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 4 |
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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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| 0.8915 | 0.1496 | 100 | 0.8518 | |
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| 0.8464 | 0.2992 | 200 | 0.8102 | |
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| 0.7874 | 0.4488 | 300 | 0.7927 | |
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| 0.7999 | 0.5984 | 400 | 0.7814 | |
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| 0.7901 | 0.7479 | 500 | 0.7731 | |
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| 0.7801 | 0.8975 | 600 | 0.7647 | |
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| 0.7585 | 1.0471 | 700 | 0.7639 | |
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| 0.7592 | 1.1967 | 800 | 0.7576 | |
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| 0.7431 | 1.3463 | 900 | 0.7542 | |
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| 0.7555 | 1.4959 | 1000 | 0.7501 | |
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| 0.7354 | 1.6455 | 1100 | 0.7456 | |
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| 0.7281 | 1.7951 | 1200 | 0.7422 | |
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| 0.7312 | 1.9447 | 1300 | 0.7395 | |
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| 0.6984 | 2.0942 | 1400 | 0.7389 | |
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| 0.7037 | 2.2438 | 1500 | 0.7382 | |
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| 0.6913 | 2.3934 | 1600 | 0.7357 | |
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| 0.7229 | 2.5430 | 1700 | 0.7341 | |
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| 0.7095 | 2.6926 | 1800 | 0.7326 | |
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| 0.6994 | 2.8422 | 1900 | 0.7319 | |
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| 0.6995 | 2.9918 | 2000 | 0.7298 | |
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| 0.6887 | 3.1414 | 2100 | 0.7314 | |
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| 0.6712 | 3.2909 | 2200 | 0.7308 | |
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| 0.6867 | 3.4405 | 2300 | 0.7300 | |
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| 0.6817 | 3.5901 | 2400 | 0.7299 | |
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| 0.681 | 3.7397 | 2500 | 0.7296 | |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.46.3 |
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- Pytorch 2.4.1+cu118 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
