metadata
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner-football_final
results: []
bert-finetuned-ner-football_final
This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1473
- Precision: 0.8997
- Recall: 0.9311
- F1: 0.9151
- Accuracy: 0.9721
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 199 | 0.1382 | 0.8850 | 0.9270 | 0.9055 | 0.9701 |
| No log | 2.0 | 398 | 0.1359 | 0.9080 | 0.9250 | 0.9164 | 0.9706 |
| 0.0325 | 3.0 | 597 | 0.1473 | 0.8997 | 0.9311 | 0.9151 | 0.9721 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.2
- Datasets 2.19.1
- Tokenizers 0.19.1