---
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: SciBERT_25K_steps_bs64
  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. -->

# SciBERT_25K_steps_bs64

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: 0.0177
- Accuracy: 0.9941
- Precision: 0.7990
- Recall: 0.5288
- F1: 0.6364
- Hamming: 0.0059

## 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: 1e-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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 0.0467        | 0.16  | 5000  | 0.0416          | 0.9902   | 0.0       | 0.0    | 0.0    | 0.0098  |
| 0.0236        | 0.32  | 10000 | 0.0223          | 0.9932   | 0.8192    | 0.3929 | 0.5311 | 0.0068  |
| 0.0198        | 0.47  | 15000 | 0.0190          | 0.9939   | 0.8015    | 0.4934 | 0.6108 | 0.0061  |
| 0.0185        | 0.63  | 20000 | 0.0180          | 0.9940   | 0.7974    | 0.5220 | 0.6310 | 0.0060  |
| 0.0181        | 0.79  | 25000 | 0.0177          | 0.9941   | 0.7990    | 0.5288 | 0.6364 | 0.0059  |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.7.1
- Tokenizers 0.14.1