llama2-7b-rust-finetune
This model is a fine-tuned version of codellama/CodeLlama-7b-hf on the-stack-rust-clean dataset. It achieves the following results on the evaluation set:
- Loss: 0.5347
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: 2.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 500
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.0 | 100 | 0.5443 |
No log | 0.01 | 200 | 0.5385 |
No log | 0.01 | 300 | 0.5362 |
No log | 0.01 | 400 | 0.5351 |
0.5389 | 0.02 | 500 | 0.5347 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
Model tree for alphahg/CodeLllama-7b-rust-finetune-qlora
Base model
codellama/CodeLlama-7b-hf