---
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: 0.5640
- Accuracy: 0.7795

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

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.184         | 0.0770 | 100  | 0.9294          | 0.6612   |
| 0.8519        | 0.1540 | 200  | 0.8007          | 0.7087   |
| 0.7555        | 0.2309 | 300  | 0.7204          | 0.7245   |
| 0.7065        | 0.3079 | 400  | 0.7121          | 0.7324   |
| 0.6499        | 0.3849 | 500  | 0.6654          | 0.7567   |
| 0.6504        | 0.4619 | 600  | 0.6227          | 0.7659   |
| 0.6421        | 0.5389 | 700  | 0.6104          | 0.7695   |
| 0.6298        | 0.6159 | 800  | 0.6094          | 0.7652   |
| 0.5851        | 0.6928 | 900  | 0.5852          | 0.7795   |
| 0.5903        | 0.7698 | 1000 | 0.5759          | 0.7828   |
| 0.5682        | 0.8468 | 1100 | 0.5769          | 0.7758   |
| 0.5809        | 0.9238 | 1200 | 0.5640          | 0.7795   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1