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# gpt2-finetuned-ner

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6671
- Precision: 0.6051
- Recall: 0.5135
- F1: 0.5556
- Accuracy: 0.8962

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 23   | 2.0585          | 0.0448    | 0.2703 | 0.0769 | 0.2815   |
| No log        | 2.0   | 46   | 0.7904          | 0.0       | 0.0    | 0.0    | 0.8444   |
| No log        | 3.0   | 69   | 0.6555          | 0.24      | 0.0324 | 0.0571 | 0.8450   |
| No log        | 4.0   | 92   | 0.6181          | 0.3504    | 0.2216 | 0.2715 | 0.8534   |
| No log        | 5.0   | 115  | 0.5701          | 0.4483    | 0.2811 | 0.3455 | 0.8671   |
| No log        | 6.0   | 138  | 0.5416          | 0.4818    | 0.3568 | 0.4099 | 0.8742   |
| No log        | 7.0   | 161  | 0.5311          | 0.4641    | 0.3838 | 0.4201 | 0.8748   |
| No log        | 8.0   | 184  | 0.5186          | 0.4938    | 0.4270 | 0.4580 | 0.8800   |
| No log        | 9.0   | 207  | 0.5574          | 0.5448    | 0.3946 | 0.4577 | 0.8859   |
| No log        | 10.0  | 230  | 0.5245          | 0.5226    | 0.4378 | 0.4765 | 0.8839   |
| No log        | 11.0  | 253  | 0.5400          | 0.5436    | 0.4378 | 0.4850 | 0.8898   |
| No log        | 12.0  | 276  | 0.5290          | 0.4880    | 0.4378 | 0.4615 | 0.8826   |
| No log        | 13.0  | 299  | 0.5426          | 0.5467    | 0.4432 | 0.4896 | 0.8891   |
| No log        | 14.0  | 322  | 0.5524          | 0.5714    | 0.4541 | 0.5060 | 0.8898   |
| No log        | 15.0  | 345  | 0.5444          | 0.5802    | 0.5081 | 0.5418 | 0.8936   |
| No log        | 16.0  | 368  | 0.5383          | 0.5706    | 0.5027 | 0.5345 | 0.8917   |
| No log        | 17.0  | 391  | 0.5427          | 0.5839    | 0.5081 | 0.5434 | 0.8936   |
| No log        | 18.0  | 414  | 0.5573          | 0.5758    | 0.5135 | 0.5429 | 0.8930   |
| No log        | 19.0  | 437  | 0.5695          | 0.5860    | 0.4973 | 0.5380 | 0.8943   |
| No log        | 20.0  | 460  | 0.5657          | 0.5802    | 0.5081 | 0.5418 | 0.8943   |
| No log        | 21.0  | 483  | 0.5815          | 0.6025    | 0.5243 | 0.5607 | 0.8962   |
| 0.6194        | 22.0  | 506  | 0.5836          | 0.5860    | 0.4973 | 0.5380 | 0.8936   |
| 0.6194        | 23.0  | 529  | 0.5937          | 0.6259    | 0.4973 | 0.5542 | 0.8969   |
| 0.6194        | 24.0  | 552  | 0.6034          | 0.6184    | 0.5081 | 0.5579 | 0.8975   |
| 0.6194        | 25.0  | 575  | 0.5804          | 0.6038    | 0.5189 | 0.5581 | 0.8969   |
| 0.6194        | 26.0  | 598  | 0.6122          | 0.625     | 0.5135 | 0.5638 | 0.8988   |
| 0.6194        | 27.0  | 621  | 0.6078          | 0.5987    | 0.5081 | 0.5497 | 0.8969   |
| 0.6194        | 28.0  | 644  | 0.6027          | 0.5988    | 0.5243 | 0.5591 | 0.8962   |
| 0.6194        | 29.0  | 667  | 0.6138          | 0.6       | 0.5189 | 0.5565 | 0.8988   |
| 0.6194        | 30.0  | 690  | 0.6118          | 0.6012    | 0.5297 | 0.5632 | 0.8975   |
| 0.6194        | 31.0  | 713  | 0.6226          | 0.6051    | 0.5135 | 0.5556 | 0.8962   |
| 0.6194        | 32.0  | 736  | 0.6149          | 0.5975    | 0.5135 | 0.5523 | 0.8962   |
| 0.6194        | 33.0  | 759  | 0.6184          | 0.5949    | 0.5081 | 0.5481 | 0.8923   |
| 0.6194        | 34.0  | 782  | 0.6251          | 0.6025    | 0.5243 | 0.5607 | 0.8975   |
| 0.6194        | 35.0  | 805  | 0.6379          | 0.6129    | 0.5135 | 0.5588 | 0.8969   |
| 0.6194        | 36.0  | 828  | 0.6439          | 0.6062    | 0.5243 | 0.5623 | 0.8969   |
| 0.6194        | 37.0  | 851  | 0.6494          | 0.6026    | 0.5081 | 0.5513 | 0.8962   |
| 0.6194        | 38.0  | 874  | 0.6426          | 0.6090    | 0.5135 | 0.5572 | 0.8969   |
| 0.6194        | 39.0  | 897  | 0.6328          | 0.6012    | 0.5297 | 0.5632 | 0.8975   |
| 0.6194        | 40.0  | 920  | 0.6517          | 0.6078    | 0.5027 | 0.5503 | 0.8949   |
| 0.6194        | 41.0  | 943  | 0.6582          | 0.6115    | 0.5189 | 0.5614 | 0.8962   |
| 0.6194        | 42.0  | 966  | 0.6556          | 0.5901    | 0.5135 | 0.5491 | 0.8943   |
| 0.6194        | 43.0  | 989  | 0.6571          | 0.6       | 0.5189 | 0.5565 | 0.8956   |
| 0.0843        | 44.0  | 1012 | 0.6609          | 0.5988    | 0.5243 | 0.5591 | 0.8962   |
| 0.0843        | 45.0  | 1035 | 0.6661          | 0.6087    | 0.5297 | 0.5665 | 0.8975   |
| 0.0843        | 46.0  | 1058 | 0.6597          | 0.5951    | 0.5243 | 0.5575 | 0.8962   |
| 0.0843        | 47.0  | 1081 | 0.6582          | 0.5963    | 0.5189 | 0.5549 | 0.8949   |
| 0.0843        | 48.0  | 1104 | 0.6609          | 0.5938    | 0.5135 | 0.5507 | 0.8943   |
| 0.0843        | 49.0  | 1127 | 0.6665          | 0.6051    | 0.5135 | 0.5556 | 0.8962   |
| 0.0843        | 50.0  | 1150 | 0.6671          | 0.6051    | 0.5135 | 0.5556 | 0.8962   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "gpt2", "model-index": [{"name": "gpt2-finetuned-ner", "results": []}]}
transformers tensorboard safetensors gpt2 token-classification generated_from_trainer base_model:gpt2 license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us