---
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
model-index:
- name: scibert_scivocab_uncased-finetuned-molstm-lpm-0.3-25epochs
  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. -->

# scibert_scivocab_uncased-finetuned-molstm-lpm-0.3-25epochs

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: 0.0407

## 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: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.1073        | 1.0   | 3301  | 0.0633          |
| 0.0657        | 2.0   | 6602  | 0.0563          |
| 0.059         | 3.0   | 9903  | 0.0536          |
| 0.0556        | 4.0   | 13204 | 0.0518          |
| 0.0531        | 5.0   | 16505 | 0.0496          |
| 0.0511        | 6.0   | 19806 | 0.0489          |
| 0.0498        | 7.0   | 23107 | 0.0477          |
| 0.0488        | 8.0   | 26408 | 0.0468          |
| 0.0478        | 9.0   | 29709 | 0.0464          |
| 0.0467        | 10.0  | 33010 | 0.0455          |
| 0.0467        | 11.0  | 36311 | 0.0450          |
| 0.0458        | 12.0  | 39612 | 0.0454          |
| 0.0449        | 13.0  | 42913 | 0.0441          |
| 0.0447        | 14.0  | 46214 | 0.0432          |
| 0.044         | 15.0  | 49515 | 0.0428          |
| 0.0436        | 16.0  | 52816 | 0.0429          |
| 0.0433        | 17.0  | 56117 | 0.0428          |
| 0.0431        | 18.0  | 59418 | 0.0423          |
| 0.0427        | 19.0  | 62719 | 0.0419          |
| 0.0425        | 20.0  | 66020 | 0.0420          |
| 0.0422        | 21.0  | 69321 | 0.0412          |
| 0.0422        | 22.0  | 72622 | 0.0413          |
| 0.0416        | 23.0  | 75923 | 0.0407          |
| 0.0415        | 24.0  | 79224 | 0.0410          |
| 0.0411        | 25.0  | 82525 | 0.0408          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2