Instructions to use ypl/outputs_gptq_training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ypl/outputs_gptq_training with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TheBloke/zephyr-7B-beta-GPTQ") model = PeftModel.from_pretrained(base_model, "ypl/outputs_gptq_training") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- README.md +7 -4
- adapter_config.json +2 -2
- adapter_model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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This model is a fine-tuned version of [TheBloke/zephyr-7B-beta-GPTQ](https://huggingface.co/TheBloke/zephyr-7B-beta-GPTQ) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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## Model description
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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: 1
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- training_steps:
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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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### Framework versions
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This model is a fine-tuned version of [TheBloke/zephyr-7B-beta-GPTQ](https://huggingface.co/TheBloke/zephyr-7B-beta-GPTQ) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2808
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## Model description
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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: 1
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- training_steps: 500
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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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| 0.3461 | 0.01 | 100 | 0.3273 |
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| 0.2884 | 0.01 | 200 | 0.2983 |
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| 0.2665 | 0.02 | 300 | 0.2891 |
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| 0.2841 | 0.03 | 400 | 0.2835 |
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| 0.2649 | 0.03 | 500 | 0.2808 |
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### Framework versions
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adapter_config.json
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"revision": null,
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"target_modules": [
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"k_proj",
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"v_proj",
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"o_proj"
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"q_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_rslora": false
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"revision": null,
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"target_modules": [
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"k_proj",
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"q_proj",
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"v_proj",
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"o_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_rslora": false
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adapter_model.safetensors
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training_args.bin
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