File size: 1,334 Bytes
8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 8a355d1 c9dad86 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
datasets:
- conll2003
model-index:
- name: bert-finetuned-ner4
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. -->
# bert-finetuned-ner4
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0775
- eval_precision: 0.9251
- eval_recall: 0.9460
- eval_f1: 0.9354
- eval_accuracy: 0.9841
- eval_runtime: 9.2322
- eval_samples_per_second: 352.028
- eval_steps_per_second: 44.085
- epoch: 1.0
- step: 1756
## 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
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
|