metadata
library_name: transformers
license: apache-2.0
base_model: ae-314/token_classification_wnut_model
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: token_classification_wnut_model
results: []
token_classification_wnut_model
This model is a fine-tuned version of ae-314/token_classification_wnut_model on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3924
- Precision: 0.5017
- Recall: 0.4124
- F1: 0.4527
- Accuracy: 0.9446
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: 1e-09
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 213 | 0.3924 | 0.5017 | 0.4124 | 0.4527 | 0.9446 |
| No log | 2.0 | 426 | 0.3924 | 0.5017 | 0.4124 | 0.4527 | 0.9446 |
| 0.0022 | 3.0 | 639 | 0.3924 | 0.5017 | 0.4124 | 0.4527 | 0.9446 |
| 0.0022 | 4.0 | 852 | 0.3924 | 0.5017 | 0.4124 | 0.4527 | 0.9446 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1