phi-2
This model is a fine-tuned version of microsoftl on the GEM/viggo dataset. It achieves the following results on the evaluation set:
- Loss: 0.2330
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: 2.5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 1000
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.917 | 0.04 | 50 | 1.4649 |
0.7037 | 0.08 | 100 | 0.4905 |
0.4209 | 0.12 | 150 | 0.3564 |
0.3534 | 0.16 | 200 | 0.3127 |
0.311 | 0.2 | 250 | 0.2940 |
0.2944 | 0.24 | 300 | 0.2798 |
0.2838 | 0.27 | 350 | 0.2710 |
0.2744 | 0.31 | 400 | 0.2634 |
0.2657 | 0.35 | 450 | 0.2577 |
0.2692 | 0.39 | 500 | 0.2513 |
0.263 | 0.43 | 550 | 0.2475 |
0.2664 | 0.47 | 600 | 0.2451 |
0.2535 | 0.51 | 650 | 0.2421 |
0.2594 | 0.55 | 700 | 0.2396 |
0.234 | 0.59 | 750 | 0.2379 |
0.2383 | 0.63 | 800 | 0.2361 |
0.2419 | 0.67 | 850 | 0.2350 |
0.2448 | 0.71 | 900 | 0.2337 |
0.241 | 0.74 | 950 | 0.2332 |
0.219 | 0.78 | 1000 | 0.2330 |
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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