| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - wnut_17 |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: token_classification_finetune |
| | results: |
| | - task: |
| | name: Token Classification |
| | type: token-classification |
| | dataset: |
| | name: wnut_17 |
| | type: wnut_17 |
| | config: wnut_17 |
| | split: test |
| | args: wnut_17 |
| | metrics: |
| | - name: Precision |
| | type: precision |
| | value: 0.5759878419452887 |
| | - name: Recall |
| | type: recall |
| | value: 0.35125115848007415 |
| | - name: F1 |
| | type: f1 |
| | value: 0.436384571099597 |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.9444206926036768 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # token_classification_finetune |
| |
|
| | This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the wnut_17 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2489 |
| | - Precision: 0.5760 |
| | - Recall: 0.3513 |
| | - F1: 0.4364 |
| | - Accuracy: 0.9444 |
| | |
| | ## 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: 2 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 1.0 | 107 | 0.2573 | 0.6011 | 0.3003 | 0.4005 | 0.9409 | |
| | | No log | 2.0 | 214 | 0.2489 | 0.5760 | 0.3513 | 0.4364 | 0.9444 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.29.2 |
| | - Pytorch 2.0.1+cu117 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.3 |
| | |
