phi-1_5-lora-tuned-sft-dolly_hitesh
This model is a fine-tuned version of microsoft/phi-1_5 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 2.3164
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Hardware
Trained model on Intel Max 1550 GPU
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: 1480
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.8614 | 1.6129 | 100 | 2.6779 |
2.6089 | 3.2258 | 200 | 2.5131 |
2.5117 | 4.8387 | 300 | 2.4545 |
2.4636 | 6.4516 | 400 | 2.4229 |
2.4367 | 8.0645 | 500 | 2.3990 |
2.4091 | 9.6774 | 600 | 2.3761 |
2.389 | 11.2903 | 700 | 2.3553 |
2.3639 | 12.9032 | 800 | 2.3394 |
2.3541 | 14.5161 | 900 | 2.3299 |
2.3418 | 16.1290 | 1000 | 2.3241 |
2.3395 | 17.7419 | 1100 | 2.3209 |
2.3319 | 19.3548 | 1200 | 2.3186 |
2.3363 | 20.9677 | 1300 | 2.3171 |
2.3327 | 22.5806 | 1400 | 2.3164 |
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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Model tree for HiteshJ14/phi-1_5-lora-tuned-sft-dolly_hitesh
Base model
microsoft/phi-1_5