metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distil_train_token_classification
results: []
distil_train_token_classification
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5326
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8057
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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.5671 | 1.0 | 7361 | 0.5711 | 0.0 | 0.0 | 0.0 | 0.7773 |
| 0.4769 | 2.0 | 14722 | 0.5131 | 0.0 | 0.0 | 0.0 | 0.7981 |
| 0.4157 | 3.0 | 22083 | 0.5135 | 0.0 | 0.0 | 0.0 | 0.8037 |
| 0.3529 | 4.0 | 29444 | 0.5326 | 0.0 | 0.0 | 0.0 | 0.8057 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0