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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
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-ner
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0209
- Precision: 0.8249
- Recall: 0.8825
- F1: 0.8527
- Accuracy: 0.9946
- B-location-precision: 0.9446
- B-location-recall: 0.9653
- B-location-f1: 0.9549
- I-location-precision: 0.9358
- I-location-recall: 0.9745
- I-location-f1: 0.9548
- B-group-precision: 0.8819
- B-group-recall: 0.8485
- B-group-f1: 0.8649
- I-group-precision: 0.8879
- I-group-recall: 0.8358
- I-group-f1: 0.8610
- B-corporation-precision: 0.8475
- B-corporation-recall: 0.8552
- B-corporation-f1: 0.8514
- I-corporation-precision: 0.8158
- I-corporation-recall: 0.7294
- I-corporation-f1: 0.7702
- B-person-precision: 0.9583
- B-person-recall: 0.9742
- B-person-f1: 0.9662
- I-person-precision: 0.9596
- I-person-recall: 0.95
- I-person-f1: 0.9548
- B-creative-work-precision: 0.8102
- B-creative-work-recall: 0.7929
- B-creative-work-f1: 0.8014
- I-creative-work-precision: 0.8131
- I-creative-work-recall: 0.8354
- I-creative-work-f1: 0.8241
- B-product-precision: 0.8682
- B-product-recall: 0.7887
- B-product-f1: 0.8266
- I-product-precision: 0.8862
- I-product-recall: 0.8886
- I-product-f1: 0.8874
- Corporation-precision: 0.6972
- Corporation-recall: 0.7919
- Corporation-f1: 0.7415
- Corporation-number: 221
- Creative-work-precision: 0.6433
- Creative-work-recall: 0.7214
- Creative-work-f1: 0.6801
- Creative-work-number: 140
- Group-precision: 0.7465
- Group-recall: 0.8144
- Group-f1: 0.7790
- Group-number: 264
- Location-precision: 0.9026
- Location-recall: 0.9471
- Location-f1: 0.9243
- Location-number: 548
- Person-precision: 0.9101
- Person-recall: 0.9515
- Person-f1: 0.9304
- Person-number: 660
- Product-precision: 0.6908
- Product-recall: 0.7394
- Product-f1: 0.7143
- Product-number: 142
## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- 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 | B-location-precision | B-location-recall | B-location-f1 | I-location-precision | I-location-recall | I-location-f1 | B-group-precision | B-group-recall | B-group-f1 | I-group-precision | I-group-recall | I-group-f1 | B-corporation-precision | B-corporation-recall | B-corporation-f1 | I-corporation-precision | I-corporation-recall | I-corporation-f1 | B-person-precision | B-person-recall | B-person-f1 | I-person-precision | I-person-recall | I-person-f1 | B-creative-work-precision | B-creative-work-recall | B-creative-work-f1 | I-creative-work-precision | I-creative-work-recall | I-creative-work-f1 | B-product-precision | B-product-recall | B-product-f1 | I-product-precision | I-product-recall | I-product-f1 | Corporation-precision | Corporation-recall | Corporation-f1 | Corporation-number | Creative-work-precision | Creative-work-recall | Creative-work-f1 | Creative-work-number | Group-precision | Group-recall | Group-f1 | Group-number | Location-precision | Location-recall | Location-f1 | Location-number | Person-precision | Person-recall | Person-f1 | Person-number | Product-precision | Product-recall | Product-f1 | Product-number |
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| No log | 1.0 | 107 | 0.1175 | 0.5693 | 0.4076 | 0.4751 | 0.9701 | 0.6320 | 0.7646 | 0.6920 | 0.7752 | 0.3929 | 0.5215 | 1.0 | 0.0114 | 0.0225 | 0.6667 | 0.0176 | 0.0343 | 0.9787 | 0.2081 | 0.3433 | nan | 0.0 | nan | 0.8123 | 0.7409 | 0.7750 | 0.9117 | 0.555 | 0.6900 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | 0.9787 | 0.2081 | 0.3433 | 221 | 0.0 | 0.0 | 0.0 | 140 | 0.3333 | 0.0152 | 0.0290 | 264 | 0.4682 | 0.6040 | 0.5275 | 548 | 0.6543 | 0.6424 | 0.6483 | 660 | 0.0 | 0.0 | 0.0 | 142 |
| No log | 2.0 | 214 | 0.0411 | 0.6931 | 0.7489 | 0.7199 | 0.9886 | 0.8194 | 0.9270 | 0.8699 | 0.8701 | 0.9214 | 0.8950 | 0.7919 | 0.5909 | 0.6768 | 0.6897 | 0.7625 | 0.7242 | 0.8297 | 0.6833 | 0.7494 | 0.8548 | 0.3118 | 0.4569 | 0.9139 | 0.9485 | 0.9309 | 0.8996 | 0.9075 | 0.9035 | 0.7541 | 0.3286 | 0.4577 | 0.7952 | 0.5091 | 0.6208 | 0.7407 | 0.5634 | 0.64 | 0.6740 | 0.8315 | 0.7445 | 0.6515 | 0.5837 | 0.6158 | 221 | 0.2941 | 0.2143 | 0.2479 | 140 | 0.5051 | 0.5682 | 0.5348 | 264 | 0.7617 | 0.8923 | 0.8218 | 548 | 0.8470 | 0.9227 | 0.8832 | 660 | 0.4091 | 0.5070 | 0.4528 | 142 |
| No log | 3.0 | 321 | 0.0209 | 0.8249 | 0.8825 | 0.8527 | 0.9946 | 0.9446 | 0.9653 | 0.9549 | 0.9358 | 0.9745 | 0.9548 | 0.8819 | 0.8485 | 0.8649 | 0.8879 | 0.8358 | 0.8610 | 0.8475 | 0.8552 | 0.8514 | 0.8158 | 0.7294 | 0.7702 | 0.9583 | 0.9742 | 0.9662 | 0.9596 | 0.95 | 0.9548 | 0.8102 | 0.7929 | 0.8014 | 0.8131 | 0.8354 | 0.8241 | 0.8682 | 0.7887 | 0.8266 | 0.8862 | 0.8886 | 0.8874 | 0.6972 | 0.7919 | 0.7415 | 221 | 0.6433 | 0.7214 | 0.6801 | 140 | 0.7465 | 0.8144 | 0.7790 | 264 | 0.9026 | 0.9471 | 0.9243 | 548 | 0.9101 | 0.9515 | 0.9304 | 660 | 0.6908 | 0.7394 | 0.7143 | 142 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cpu
- Datasets 2.14.6
- Tokenizers 0.14.1
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