finetuned
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: 0.2803
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: 1
- 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_ratio: 0.1
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.5282 | 0.3410 | 100 | 0.4418 |
0.3992 | 0.6820 | 200 | 0.3800 |
0.3324 | 1.0230 | 300 | 0.3341 |
0.3127 | 1.3640 | 400 | 0.3147 |
0.2591 | 1.7050 | 500 | 0.2895 |
0.2621 | 2.0460 | 600 | 0.2926 |
0.2195 | 2.3870 | 700 | 0.2826 |
0.2225 | 2.7280 | 800 | 0.2803 |
Framework versions
- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for msahabudinov/finetuned
Base model
microsoft/Phi-3.5-mini-instruct