Llama2-7B-lora-r-32-generic-step-300-lr-1e-5-labels_40.0
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.4216
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- training_steps: 300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.5819 | 0.3653 | 20 | 5.4958 |
| 4.7648 | 0.7306 | 40 | 4.7448 |
| 4.2831 | 1.0959 | 60 | 4.2523 |
| 4.038 | 1.4612 | 80 | 3.9900 |
| 3.8178 | 1.8265 | 100 | 3.8157 |
| 3.6619 | 2.1918 | 120 | 3.6964 |
| 3.6132 | 2.5571 | 140 | 3.6111 |
| 3.565 | 2.9224 | 160 | 3.5456 |
| 3.4816 | 3.2877 | 180 | 3.4973 |
| 3.4398 | 3.6530 | 200 | 3.4669 |
| 3.5158 | 4.0183 | 220 | 3.4454 |
| 3.4244 | 4.3836 | 240 | 3.4324 |
| 3.3979 | 4.7489 | 260 | 3.4250 |
| 3.4238 | 5.1142 | 280 | 3.4220 |
| 3.428 | 5.4795 | 300 | 3.4216 |
Framework versions
- PEFT 0.15.2
- Transformers 4.45.2
- Pytorch 2.5.0+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
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Model tree for Siqi-Hu/Llama2-7B-lora-r-32-generic-step-300-lr-1e-5-labels_40.0
Base model
meta-llama/Llama-2-7b-hf