transformers pytorch bert text-classification generated_from_trainer dataset:scicite base_model:allenai/scibert_scivocab_uncased base_model:finetune:allenai/scibert_scivocab_uncased model-index autotrain_compatible endpoints_compatible region:us
---
base_model: allenai/scibert_scivocab_uncased
datasets:
- scicite
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: Scicite_classification_model
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: scicite
      type: scicite
      config: default
      split: validation
      args: default
    metrics:
    - type: accuracy
      value: 0.9224890829694323
      name: Accuracy
---

<!-- 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. -->

# Scicite_classification_model

This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the scicite dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4704
- Accuracy: 0.9225

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2493        | 1.0   | 513  | 0.2034          | 0.9214   |
| 0.1777        | 2.0   | 1026 | 0.1942          | 0.9247   |
| 0.1385        | 3.0   | 1539 | 0.2552          | 0.9247   |
| 0.1019        | 4.0   | 2052 | 0.2995          | 0.9258   |
| 0.0705        | 5.0   | 2565 | 0.3964          | 0.9181   |
| 0.0444        | 6.0   | 3078 | 0.4243          | 0.9203   |
| 0.0331        | 7.0   | 3591 | 0.4904          | 0.9192   |
| 0.0223        | 8.0   | 4104 | 0.4704          | 0.9225   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
