binary_classification
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3251
- Accuracy: 0.5
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 12 | 0.6405 | 0.8 |
No log | 2.0 | 24 | 1.2785 | 0.5 |
No log | 3.0 | 36 | 0.7415 | 0.7 |
No log | 4.0 | 48 | 0.9357 | 0.5 |
No log | 5.0 | 60 | 1.2000 | 0.6 |
No log | 6.0 | 72 | 1.4307 | 0.6 |
No log | 7.0 | 84 | 1.3643 | 0.5 |
No log | 8.0 | 96 | 1.2574 | 0.5 |
No log | 9.0 | 108 | 1.5340 | 0.5 |
No log | 10.0 | 120 | 1.3251 | 0.5 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.15.1
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Model tree for phdatdt/binary_classification
Base model
mistralai/Mistral-7B-v0.1