llama2-docsum-adapter
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4782
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.71 | 0.4 | 200 | 1.4977 |
1.7529 | 0.8 | 400 | 1.4883 |
1.1946 | 1.2 | 600 | 1.4800 |
1.6962 | 1.6 | 800 | 1.4786 |
1.1067 | 2.0 | 1000 | 1.4782 |
Framework versions
- PEFT 0.13.1.dev0
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1
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Model tree for AvniMittal13/llama2-docsum-adapter
Base model
microsoft/phi-2