| | --- |
| | 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_2 |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # distil_train_token_classification_2 |
| |
|
| | This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7646 |
| | - Precision: 0.0 |
| | - Recall: 0.0 |
| | - F1: 0.0 |
| | - Accuracy: 0.8112 |
| |
|
| | ## 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: 8e-05 |
| | - train_batch_size: 32 |
| | - 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: 6 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:---:|:--------:| |
| | | 0.5429 | 1.0 | 3681 | 0.5346 | 0.0 | 0.0 | 0.0 | 0.7848 | |
| | | 0.4387 | 2.0 | 7362 | 0.5033 | 0.0 | 0.0 | 0.0 | 0.8034 | |
| | | 0.3288 | 3.0 | 11043 | 0.4983 | 0.0 | 0.0 | 0.0 | 0.8101 | |
| | | 0.2436 | 4.0 | 14724 | 0.5736 | 0.0 | 0.0 | 0.0 | 0.8086 | |
| | | 0.1677 | 5.0 | 18405 | 0.6681 | 0.0 | 0.0 | 0.0 | 0.8107 | |
| | | 0.1162 | 6.0 | 22086 | 0.7646 | 0.0 | 0.0 | 0.0 | 0.8112 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.34.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.14.0 |
| | |
