File size: 1,880 Bytes
a3bc07a |
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 63 64 65 66 67 68 69 70 71 |
---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-ner-chunks
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-ner-chunks
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2207
- Precision: 0.8917
- Recall: 0.9214
- F1: 0.9063
- Accuracy: 0.9730
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.077 | 1.0 | 1756 | 0.0741 | 0.9068 | 0.9334 | 0.9199 | 0.9795 |
| 0.0443 | 2.0 | 3512 | 0.0649 | 0.9172 | 0.9428 | 0.9298 | 0.9841 |
| 0.0265 | 3.0 | 5268 | 0.0578 | 0.9250 | 0.9488 | 0.9368 | 0.9863 |
| 0.0109 | 4.0 | 7024 | 0.0651 | 0.9347 | 0.9492 | 0.9419 | 0.9866 |
| 0.005 | 5.0 | 8780 | 0.0692 | 0.9354 | 0.9502 | 0.9427 | 0.9869 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
|