diwakar21scout
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diwakar21scout/llama-pls/sql-pyspark_v0
Browse files- README.md +80 -0
- adapter_config.json +19 -0
- adapter_model.bin +3 -0
- training_args.bin +3 -0
README.md
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---
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license: llama2
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base_model: codellama/CodeLlama-7b-hf
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tags:
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- generated_from_trainer
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model-index:
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- name: sql-code-llama
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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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# sql-code-llama
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This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0810
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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: 0.0003
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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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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: 100
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- training_steps: 400
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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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| 2.033 | 0.28 | 20 | 1.9418 |
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| 1.3136 | 0.56 | 40 | 0.8477 |
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| 0.1674 | 0.83 | 60 | 0.1384 |
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| 0.1276 | 1.11 | 80 | 0.1220 |
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| 0.1106 | 1.39 | 100 | 0.1046 |
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| 0.102 | 1.67 | 120 | 0.0946 |
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| 0.0917 | 1.94 | 140 | 0.0903 |
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| 0.0895 | 2.22 | 160 | 0.0887 |
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| 0.0889 | 2.5 | 180 | 0.0872 |
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| 0.0874 | 2.78 | 200 | 0.0858 |
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| 0.086 | 3.06 | 220 | 0.0851 |
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| 0.0861 | 3.33 | 240 | 0.0842 |
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| 0.085 | 3.61 | 260 | 0.0835 |
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| 0.0821 | 3.89 | 280 | 0.0830 |
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| 0.0838 | 4.17 | 300 | 0.0823 |
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| 0.0816 | 4.44 | 320 | 0.0820 |
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| 0.0785 | 4.72 | 340 | 0.0815 |
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| 0.0819 | 5.0 | 360 | 0.0812 |
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| 0.081 | 5.28 | 380 | 0.0810 |
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| 0.0765 | 5.56 | 400 | 0.0810 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.15.0
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adapter_config.json
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{
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"base_model_name_or_path": "codellama/CodeLlama-7b-hf",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"lora_alpha": 16,
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"lora_dropout": 0.05,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 16,
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"target_modules": [
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"q_proj",
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"k_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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}
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:e5e1621f48d9ad8feb1d6d31050275f0aafd080c5c07153301fe2f48411f4406
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size 443
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:bfaadddc9621cf3dfc6e89dad1321ab1417b56cf9f00b6968d4009230e4ec47b
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size 4283
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