---
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_model
  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. -->

# my_awesome_model

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: 0.3690
- Accuracy: 0.9119

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 88   | 1.0040          | 0.7528   |
| No log        | 2.0   | 176  | 0.4404          | 0.8892   |
| No log        | 3.0   | 264  | 0.3365          | 0.8977   |
| No log        | 4.0   | 352  | 0.2969          | 0.9205   |
| No log        | 5.0   | 440  | 0.3452          | 0.9034   |
| 0.594         | 6.0   | 528  | 0.3440          | 0.9091   |
| 0.594         | 7.0   | 616  | 0.3584          | 0.9119   |
| 0.594         | 8.0   | 704  | 0.3690          | 0.9119   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2