---
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: SciBERT_TwoWayLoss_25K_bs64_P10_N5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# SciBERT_TwoWayLoss_25K_bs64_P10_N5

This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 15.1250
- Accuracy: 0.7066
- Precision: 0.0321
- Recall: 0.9982
- F1: 0.0622
- Hamming: 0.2934

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 25000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     | Hamming |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 28.5732       | 0.16  | 5000  | 26.4288         | 0.6945   | 0.0307    | 0.9910 | 0.0595 | 0.3055  |
| 19.8755       | 0.32  | 10000 | 18.9620         | 0.7010   | 0.0315    | 0.9959 | 0.0610 | 0.2990  |
| 17.1294       | 0.47  | 15000 | 16.5587         | 0.7021   | 0.0316    | 0.9970 | 0.0613 | 0.2979  |
| 15.8209       | 0.63  | 20000 | 15.4919         | 0.7053   | 0.0320    | 0.9982 | 0.0620 | 0.2947  |
| 15.4304       | 0.79  | 25000 | 15.1250         | 0.7066   | 0.0321    | 0.9982 | 0.0622 | 0.2934  |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.2.0.dev20231002
- Datasets 2.7.1
- Tokenizers 0.13.3