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---
license: llama2
base_model: codellama/CodeLlama-7b-hf
tags:
- generated_from_trainer
model-index:
- name: code-llama-sparql-lcquad-large-dbpedia
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# code-llama-sparql-lcquad-large-dbpedia
This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2040
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 400
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.3087 | 0.0184 | 20 | 1.3391 |
| 1.0131 | 0.0368 | 40 | 0.7246 |
| 0.5023 | 0.0553 | 60 | 0.4406 |
| 0.4287 | 0.0737 | 80 | 0.3738 |
| 0.3432 | 0.0921 | 100 | 0.3530 |
| 0.2725 | 0.1105 | 120 | 0.3329 |
| 0.2539 | 0.1290 | 140 | 0.2888 |
| 0.2847 | 0.1474 | 160 | 0.2762 |
| 0.253 | 0.1658 | 180 | 0.2598 |
| 0.2168 | 0.1842 | 200 | 0.2480 |
| 0.2194 | 0.2027 | 220 | 0.2516 |
| 0.2123 | 0.2211 | 240 | 0.2300 |
| 0.2366 | 0.2395 | 260 | 0.2180 |
| 0.2129 | 0.2579 | 280 | 0.2181 |
| 0.2073 | 0.2764 | 300 | 0.2154 |
| 0.1992 | 0.2948 | 320 | 0.2086 |
| 0.2086 | 0.3132 | 340 | 0.2069 |
| 0.2237 | 0.3316 | 360 | 0.2056 |
| 0.1982 | 0.3501 | 380 | 0.2043 |
| 0.2039 | 0.3685 | 400 | 0.2040 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.10.1
- Tokenizers 0.19.1
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