metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: llm-selector
results: []
llm-selector
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4531
- Accuracy: 0.8794
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: 2e-05
- 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: 40
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| No log | 1.0 | 33 | 0.2763 | 1.8921 |
| No log | 2.0 | 66 | 0.2685 | 1.8425 |
| No log | 3.0 | 99 | 0.3307 | 1.8125 |
| No log | 4.0 | 132 | 0.2763 | 1.8077 |
| No log | 5.0 | 165 | 0.2685 | 1.8029 |
| No log | 6.0 | 198 | 0.2763 | 1.7951 |
| No log | 7.0 | 231 | 0.2763 | 1.7898 |
| No log | 8.0 | 264 | 0.2685 | 1.7464 |
| No log | 9.0 | 297 | 0.4630 | 1.5910 |
| No log | 10.0 | 330 | 0.4747 | 1.5129 |
| No log | 11.0 | 363 | 0.4397 | 1.4520 |
| No log | 12.0 | 396 | 0.6109 | 1.3628 |
| No log | 13.0 | 429 | 0.5914 | 1.2874 |
| No log | 14.0 | 462 | 0.6226 | 1.1989 |
| No log | 15.0 | 495 | 0.6809 | 1.1137 |
| 1.6823 | 16.0 | 528 | 0.6732 | 1.0936 |
| 1.6823 | 17.0 | 561 | 0.6887 | 1.0676 |
| 1.6823 | 18.0 | 594 | 0.7198 | 0.9726 |
| 1.6823 | 19.0 | 627 | 0.7626 | 0.9069 |
| 1.6823 | 20.0 | 660 | 0.7626 | 0.8574 |
| 1.6823 | 21.0 | 693 | 0.7860 | 0.8008 |
| 1.6823 | 22.0 | 726 | 0.7899 | 0.7594 |
| 1.6823 | 23.0 | 759 | 0.8093 | 0.7151 |
| 1.6823 | 24.0 | 792 | 0.8016 | 0.6994 |
| 1.6823 | 25.0 | 825 | 0.8016 | 0.7014 |
| 1.6823 | 26.0 | 858 | 0.8171 | 0.6543 |
| 1.6823 | 27.0 | 891 | 0.8093 | 0.6328 |
| 1.6823 | 28.0 | 924 | 0.8132 | 0.6141 |
| 1.6823 | 29.0 | 957 | 0.8288 | 0.6207 |
| 1.6823 | 30.0 | 990 | 0.8288 | 0.6070 |
| 0.8033 | 31.0 | 1023 | 0.5843 | 0.8288 |
| 0.8033 | 32.0 | 1056 | 0.5616 | 0.8521 |
| 0.8033 | 33.0 | 1089 | 0.5372 | 0.8482 |
| 0.8033 | 34.0 | 1122 | 0.5264 | 0.8482 |
| 0.8033 | 35.0 | 1155 | 0.4922 | 0.8599 |
| 0.8033 | 36.0 | 1188 | 0.4755 | 0.8716 |
| 0.8033 | 37.0 | 1221 | 0.4738 | 0.8755 |
| 0.8033 | 38.0 | 1254 | 0.4590 | 0.8794 |
| 0.8033 | 39.0 | 1287 | 0.4544 | 0.8833 |
| 0.8033 | 40.0 | 1320 | 0.4531 | 0.8794 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3