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

# impact-cat

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: 0.8264
- Accuracy: 0.725

## 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   | 40   | 1.1896          | 0.5375   |
| No log        | 2.0   | 80   | 0.6831          | 0.7      |
| No log        | 3.0   | 120  | 0.6951          | 0.7      |
| No log        | 4.0   | 160  | 0.7126          | 0.6937   |
| No log        | 5.0   | 200  | 0.7937          | 0.6875   |
| No log        | 6.0   | 240  | 0.6445          | 0.7125   |
| No log        | 7.0   | 280  | 0.7990          | 0.7188   |
| No log        | 8.0   | 320  | 0.8264          | 0.725    |


### Framework versions

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