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--- |
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license: llama2 |
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base_model: codellama/CodeLlama-7b-Instruct-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-instruct-7b-text-to-sparql-axiom |
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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-instruct-7b-text-to-sparql-axiom |
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This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1333 |
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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: 800 |
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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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| 1.3919 | 0.0710 | 20 | 1.3906 | |
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| 0.8712 | 0.1421 | 40 | 0.4591 | |
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| 0.2672 | 0.2131 | 60 | 0.2378 | |
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| 0.213 | 0.2842 | 80 | 0.2065 | |
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| 0.1697 | 0.3552 | 100 | 0.2208 | |
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| 0.2068 | 0.4263 | 120 | 0.1886 | |
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| 0.1808 | 0.4973 | 140 | 0.1843 | |
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| 0.2073 | 0.5684 | 160 | 0.1812 | |
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| 0.1833 | 0.6394 | 180 | 0.1735 | |
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| 0.1556 | 0.7105 | 200 | 0.1836 | |
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| 0.1813 | 0.7815 | 220 | 0.1688 | |
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| 0.166 | 0.8526 | 240 | 0.1642 | |
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| 0.1773 | 0.9236 | 260 | 0.1609 | |
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| 0.1514 | 0.9947 | 280 | 0.1597 | |
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| 0.1592 | 1.0657 | 300 | 0.1581 | |
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| 0.1632 | 1.1368 | 320 | 0.1552 | |
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| 0.1601 | 1.2078 | 340 | 0.1554 | |
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| 0.1529 | 1.2789 | 360 | 0.1523 | |
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| 0.1352 | 1.3499 | 380 | 0.1528 | |
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| 0.1601 | 1.4210 | 400 | 0.1496 | |
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| 0.1523 | 1.4920 | 420 | 0.1482 | |
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| 0.1568 | 1.5631 | 440 | 0.1482 | |
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| 0.1598 | 1.6341 | 460 | 0.1461 | |
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| 0.1432 | 1.7052 | 480 | 0.1471 | |
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| 0.158 | 1.7762 | 500 | 0.1430 | |
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| 0.1479 | 1.8472 | 520 | 0.1422 | |
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| 0.1488 | 1.9183 | 540 | 0.1429 | |
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| 0.1422 | 1.9893 | 560 | 0.1397 | |
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| 0.149 | 2.0604 | 580 | 0.1391 | |
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| 0.1352 | 2.1314 | 600 | 0.1381 | |
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| 0.1357 | 2.2025 | 620 | 0.1389 | |
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| 0.1519 | 2.2735 | 640 | 0.1369 | |
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| 0.1321 | 2.3446 | 660 | 0.1367 | |
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| 0.1381 | 2.4156 | 680 | 0.1361 | |
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| 0.1362 | 2.4867 | 700 | 0.1349 | |
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| 0.1329 | 2.5577 | 720 | 0.1351 | |
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| 0.1457 | 2.6288 | 740 | 0.1340 | |
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| 0.1267 | 2.6998 | 760 | 0.1336 | |
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| 0.1433 | 2.7709 | 780 | 0.1335 | |
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| 0.1343 | 2.8419 | 800 | 0.1333 | |
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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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