Llama-2-7b-hf-finetuned-py-to-cpp
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3938
Test evaluation:
- BLEU: 60.09
- COMET: 87.40
- CODEBLEU: 74.17
- N-gram match: 63.15
- Weighted n-gram match: 78.82
- Syntax match: 72.65
- Dataflow match: 82.08
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- 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
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.99 | 67 | 0.6338 |
| No log | 2.0 | 135 | 0.4313 |
| No log | 2.98 | 201 | 0.3938 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.13.3
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Model tree for hugo-albert/Llama-2-7b-hf-finetuned-py-to-cpp
Base model
meta-llama/Llama-2-7b-hf