transformers pytorch bert multiple-choice generated_from_trainer base_model:allenai/scibert_scivocab_uncased endpoints_compatible region:us
---
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Science-LLM-baseline
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Science-LLM-baseline

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: 1.6094
- Accuracy: 0.35

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 45   | 1.6094          | 0.3      |
| No log        | 2.0   | 90   | 1.6094          | 0.4      |
| No log        | 3.0   | 135  | 1.6094          | 0.35     |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
