metadata
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Test-Model
This model is a fine-tuned version of llama, and is specialized for document classification. The overall accuracy of the model is 0.978852 and the hit rate is 0.543211.
Training Parameters
Epochs: 5
Batch Size: 20
Threshold: 0.975
Token Length: 512
Data Set Size: 10000
Evenly Distributed: True
Municipalities: Heroey, Kongsberg, Boemlo, Luster, Maalselv
Learning Rate: 0.0001
Weight Decay: 0.01
Eval Accumulation Steps: 4
| Label | Accuracy | Accuracy Accumulation | Hit Rate | Hit Rate Accumulation |
|---|---|---|---|---|
| 0 | 0.93 | 0.93 | 0.98 | 0.98 |
| 1 | 0.95 | 0.95 | 0.97 | 0.97 |
| 2 | 0.91 | 0.91 | 0.98 | 0.98 |
| 3 | 0.40 | 0.40 | 0.57 | 0.57 |
| 4 | 0.25 | 0.25 | 0.63 | 0.63 |
| 5 | 0.86 | 0.86 | 0.94 | 0.94 |
| 6 | 0.99 | 0.99 | 1.04 | 1.04 |
| 7 | 0.94 | 0.94 | 0.98 | 0.98 |
| 8 | 0.67 | 0.67 | 0.86 | 0.86 |
| 9 | 0.99 | 0.99 | 0.99 | 0.99 |