Training Hardware
This model was trained using Intel GPU:
- Intel(R) Data Center GPU Max 1100
- CPU: Intel(R) Xeon(R) Platinum 8480+
phiverse-1_5-lora-tuned-dolly.sft
This model is a fine-tuned version of microsoft/phi-1_5 on the dolly 15k dataset from databricks (databricks/databricks-dolly-15k). It achieves the following results on the evaluation set:
- Loss: 2.4899
Intended uses
Text generation tasks including chatbots, content generation, and various other NLP applications.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 296
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.7682 | 1.6129 | 100 | 2.5802 |
2.5575 | 3.2258 | 200 | 2.4899 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.0.post0+cxx11.abi
- Datasets 2.19.1
- Tokenizers 0.19.1
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microsoft/phi-1_5
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