metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MC_proteome_literature_classification_balanced
results: []
MC_proteome_literature_classification_balanced
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: 3.6012
- Accuracy: 0.4382
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 263 | 2.4798 | 0.2809 |
| 2.4407 | 2.0 | 526 | 2.3829 | 0.3146 |
| 2.4407 | 3.0 | 789 | 2.3702 | 0.3146 |
| 2.2844 | 4.0 | 1052 | 2.2006 | 0.3034 |
| 2.2844 | 5.0 | 1315 | 2.0415 | 0.3933 |
| 2.2551 | 6.0 | 1578 | 2.1146 | 0.3708 |
| 2.2551 | 7.0 | 1841 | 2.4420 | 0.4045 |
| 1.7206 | 8.0 | 2104 | 2.4813 | 0.4045 |
| 1.7206 | 9.0 | 2367 | 2.1333 | 0.4494 |
| 1.2881 | 10.0 | 2630 | 2.8120 | 0.4382 |
| 1.2881 | 11.0 | 2893 | 2.7040 | 0.4607 |
| 0.9473 | 12.0 | 3156 | 3.1826 | 0.4382 |
| 0.9473 | 13.0 | 3419 | 3.1203 | 0.4157 |
| 0.5293 | 14.0 | 3682 | 3.4692 | 0.4270 |
| 0.5293 | 15.0 | 3945 | 3.6012 | 0.4382 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3