Phi-3.5-MultiCap-mt
This model is a fine-tuned version of microsoft/Phi-3.5-mini-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7569
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.4288 | 0.1533 | 15 | 1.3449 |
1.0894 | 0.3065 | 30 | 1.1240 |
0.9541 | 0.4598 | 45 | 0.9830 |
0.9216 | 0.6130 | 60 | 0.8949 |
0.8675 | 0.7663 | 75 | 0.8414 |
0.8007 | 0.9195 | 90 | 0.8108 |
0.8205 | 1.0728 | 105 | 0.7919 |
0.7864 | 1.2261 | 120 | 0.7794 |
0.7983 | 1.3793 | 135 | 0.7705 |
0.7784 | 1.5326 | 150 | 0.7641 |
0.744 | 1.6858 | 165 | 0.7595 |
0.7765 | 1.8391 | 180 | 0.7569 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for sofyc/Phi-3.5-MultiCap-mt
Base model
microsoft/Phi-3.5-mini-instruct