metadata
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distillbert-finetuned-ner-btc
results: []
distillbert-finetuned-ner-btc
This model is a fine-tuned version of distilbert/distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2802
- Precision: 0.4392
- Recall: 0.4370
- F1: 0.4381
- Accuracy: 0.9117
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 | 56 | 0.3448 | 0.4762 | 0.0345 | 0.0644 | 0.8792 |
| No log | 2.0 | 112 | 0.2880 | 0.4506 | 0.3938 | 0.4203 | 0.9080 |
| No log | 3.0 | 168 | 0.2802 | 0.4392 | 0.4370 | 0.4381 | 0.9117 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2