llama2-7b-ft-adapters
This model is a fine-tuned version of TinyPixel/Llama-2-7B-bf16-sharded on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4400
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: 16
- eval_batch_size: 8
- 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: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.2165 | 0.95 | 15 | 0.6419 |
0.505 | 1.97 | 31 | 0.4841 |
0.4416 | 2.98 | 47 | 0.4493 |
0.3976 | 4.0 | 63 | 0.4346 |
0.375 | 4.95 | 78 | 0.4301 |
0.2842 | 5.71 | 90 | 0.4400 |
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for Holmeister/llama2-7b-ft-adapters
Base model
TinyPixel/Llama-2-7B-bf16-sharded