transformers pytorch bert token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
---
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: scipaper-bert-finetuned-ner
  results: []
---

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# scipaper-bert-finetuned-ner

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0466
- F1: 0.2504

## 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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 25   | 0.0460          | 0.0    |
| No log        | 2.0   | 50   | 0.0429          | 0.0    |
| No log        | 3.0   | 75   | 0.0428          | 0.0    |
| No log        | 4.0   | 100  | 0.0416          | 0.0    |
| No log        | 5.0   | 125  | 0.0447          | 0.0596 |
| No log        | 6.0   | 150  | 0.0425          | 0.1833 |
| No log        | 7.0   | 175  | 0.0437          | 0.2607 |
| No log        | 8.0   | 200  | 0.0466          | 0.2504 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
