---
library_name: transformers
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: MatSciBERT-domain-classifier
  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. -->

# MatSciBERT-domain-classifier

This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3556
- F1: 0.9027

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 57   | 1.2446          | 0.8089 |
| 1.8516        | 2.0   | 114  | 0.6696          | 0.8354 |
| 1.8516        | 3.0   | 171  | 0.4096          | 0.8948 |
| 0.4239        | 4.0   | 228  | 0.3121          | 0.9040 |
| 0.4239        | 5.0   | 285  | 0.3556          | 0.9027 |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.21.1