metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: DistilBERT-finetuned-ner-S800
results: []
DistilBERT-finetuned-ner-S800
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0899
- Precision: 0.4198
- Recall: 0.4993
- F1: 0.4561
- Accuracy: 0.9652
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 | 55 | 0.1352 | 0.2728 | 0.3604 | 0.3106 | 0.9432 |
| No log | 2.0 | 110 | 0.0979 | 0.3912 | 0.4264 | 0.4081 | 0.9617 |
| No log | 3.0 | 165 | 0.0899 | 0.4198 | 0.4993 | 0.4561 | 0.9652 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3