vendata-train
This model is a fine-tuned version of codellama/CodeLlama-7b-Instruct-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9052
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 100
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.0633 | 0.1 | 10 | 1.0362 |
1.2685 | 0.2 | 20 | 0.9920 |
1.2542 | 0.3 | 30 | 0.9562 |
1.1031 | 0.4 | 40 | 0.9356 |
1.0196 | 0.5 | 50 | 0.9224 |
0.9397 | 0.6 | 60 | 0.9140 |
0.9485 | 0.7 | 70 | 0.9091 |
0.9506 | 0.8 | 80 | 0.9064 |
0.978 | 0.9 | 90 | 0.9054 |
1.0167 | 1.0 | 100 | 0.9052 |
Framework versions
- PEFT 0.8.2
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for SuperSecureHuman/phi-2-vendata
Base model
codellama/CodeLlama-7b-Instruct-hf