llama-7b-SFT_ds_eli5_1024_r_64_alpha_16
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: 2.1904
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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.155 | 0.3 | 97 | 2.2053 |
2.1524 | 0.6 | 194 | 2.1970 |
2.1547 | 0.9 | 291 | 2.1904 |
2.0945 | 1.2 | 388 | 2.1929 |
2.0888 | 1.5 | 485 | 2.1950 |
2.0973 | 1.8 | 582 | 2.1969 |
2.0444 | 2.1 | 679 | 2.1937 |
2.0349 | 2.4 | 776 | 2.1992 |
2.0459 | 2.7 | 873 | 2.2036 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
Model tree for dhmeltzer/llama-7b-SFT_ds_eli5_1024_r_64_alpha_16
Base model
meta-llama/Llama-2-7b-hf