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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: code-llama-sparql-lcquad-large-dbpedia |
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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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# code-llama-sparql-lcquad-large-dbpedia |
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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: 0.2040 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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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| 1.3087 | 0.0184 | 20 | 1.3391 | |
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| 1.0131 | 0.0368 | 40 | 0.7246 | |
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| 0.5023 | 0.0553 | 60 | 0.4406 | |
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| 0.4287 | 0.0737 | 80 | 0.3738 | |
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| 0.3432 | 0.0921 | 100 | 0.3530 | |
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| 0.2725 | 0.1105 | 120 | 0.3329 | |
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| 0.2539 | 0.1290 | 140 | 0.2888 | |
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| 0.2847 | 0.1474 | 160 | 0.2762 | |
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| 0.253 | 0.1658 | 180 | 0.2598 | |
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| 0.2168 | 0.1842 | 200 | 0.2480 | |
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| 0.2194 | 0.2027 | 220 | 0.2516 | |
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| 0.2123 | 0.2211 | 240 | 0.2300 | |
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| 0.2366 | 0.2395 | 260 | 0.2180 | |
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| 0.2129 | 0.2579 | 280 | 0.2181 | |
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| 0.2073 | 0.2764 | 300 | 0.2154 | |
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| 0.1992 | 0.2948 | 320 | 0.2086 | |
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| 0.2086 | 0.3132 | 340 | 0.2069 | |
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| 0.2237 | 0.3316 | 360 | 0.2056 | |
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| 0.1982 | 0.3501 | 380 | 0.2043 | |
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| 0.2039 | 0.3685 | 400 | 0.2040 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.10.1 |
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- Tokenizers 0.19.1 |
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