metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-topic-model
results: []
distilbert-base-uncased-finetuned-topic-model
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: 1.2697
- Accuracy: 0.6030
- F1: 0.5963
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: 32
- eval_batch_size: 32
- 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 | F1 |
|---|---|---|---|---|---|
| 2.7083 | 1.0 | 97 | 2.3146 | 0.4470 | 0.3978 |
| 1.9763 | 2.0 | 194 | 1.7865 | 0.5136 | 0.4576 |
| 1.5486 | 3.0 | 291 | 1.5441 | 0.5561 | 0.5263 |
| 1.2422 | 4.0 | 388 | 1.4228 | 0.5659 | 0.5410 |
| 1.0498 | 5.0 | 485 | 1.3569 | 0.5780 | 0.5600 |
| 0.9017 | 6.0 | 582 | 1.3051 | 0.6023 | 0.5909 |
| 0.8082 | 7.0 | 679 | 1.2839 | 0.6053 | 0.5973 |
| 0.7148 | 8.0 | 776 | 1.2836 | 0.5955 | 0.5890 |
| 0.6598 | 9.0 | 873 | 1.2702 | 0.6045 | 0.5961 |
| 0.6222 | 10.0 | 970 | 1.2697 | 0.6030 | 0.5963 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3