---
base_model: allenai/scibert_scivocab_cased
tags:
- generated_from_trainer
model-index:
- name: SOMD-scibert-stage2-v1
  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. -->

# SOMD-scibert-stage2-v1

This model is a fine-tuned version of [allenai/scibert_scivocab_cased](https://huggingface.co/allenai/scibert_scivocab_cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0115

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 202  | 0.4607          |
| No log        | 1.99  | 404  | 0.2408          |
| 0.5891        | 2.99  | 606  | 0.1086          |
| 0.5891        | 3.98  | 808  | 0.0879          |
| 0.1352        | 4.98  | 1010 | 0.0505          |
| 0.1352        | 5.97  | 1212 | 0.0286          |
| 0.1352        | 6.97  | 1414 | 0.0262          |
| 0.0541        | 7.96  | 1616 | 0.0231          |
| 0.0541        | 8.96  | 1818 | 0.0224          |
| 0.0395        | 9.95  | 2020 | 0.0217          |
| 0.0395        | 10.95 | 2222 | 0.0191          |
| 0.0395        | 11.94 | 2424 | 0.0156          |
| 0.0303        | 12.94 | 2626 | 0.0164          |
| 0.0303        | 13.93 | 2828 | 0.0146          |
| 0.0226        | 14.93 | 3030 | 0.0124          |
| 0.0226        | 15.92 | 3232 | 0.0127          |
| 0.0226        | 16.92 | 3434 | 0.0115          |
| 0.0176        | 17.91 | 3636 | 0.0123          |
| 0.0176        | 18.91 | 3838 | 0.0115          |
| 0.0146        | 19.9  | 4040 | 0.0115          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2