---
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: 0.5393
- Accuracy: 0.7781

## 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   | 160  | 0.4152          | 0.8406   |
| No log        | 2.0   | 320  | 0.4462          | 0.8375   |
| No log        | 3.0   | 480  | 0.4197          | 0.8203   |
| 0.511         | 4.0   | 640  | 0.4687          | 0.8453   |
| 0.511         | 5.0   | 800  | 0.4595          | 0.8328   |
| 0.511         | 6.0   | 960  | 0.4773          | 0.8047   |
| 0.2607        | 7.0   | 1120 | 0.5149          | 0.7953   |
| 0.2607        | 8.0   | 1280 | 0.5393          | 0.7781   |


### Framework versions

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