metadata
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner_twitter_fine_tune
results: []
ner_twitter_fine_tune
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: 0.4211
- Precision: 0.6078
- Recall: 0.5901
- F1: 0.5988
- Accuracy: 0.9308
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 56 | 0.3586 | 0.6358 | 0.5660 | 0.5989 | 0.9323 |
| No log | 2.0 | 112 | 0.3618 | 0.6069 | 0.5746 | 0.5903 | 0.9297 |
| No log | 3.0 | 168 | 0.3722 | 0.5956 | 0.6038 | 0.5997 | 0.9306 |
| No log | 4.0 | 224 | 0.3993 | 0.6060 | 0.5883 | 0.5970 | 0.9301 |
| No log | 5.0 | 280 | 0.4102 | 0.5411 | 0.6329 | 0.5834 | 0.9232 |
| No log | 6.0 | 336 | 0.4077 | 0.6097 | 0.5815 | 0.5953 | 0.9319 |
| No log | 7.0 | 392 | 0.4096 | 0.5858 | 0.6089 | 0.5971 | 0.9286 |
| No log | 8.0 | 448 | 0.4169 | 0.5975 | 0.5832 | 0.5903 | 0.9297 |
| 0.0111 | 9.0 | 504 | 0.4208 | 0.6064 | 0.5866 | 0.5963 | 0.9309 |
| 0.0111 | 10.0 | 560 | 0.4211 | 0.6078 | 0.5901 | 0.5988 | 0.9308 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.0
- Tokenizers 0.15.2