transformers pytorch tensorboard big_bird multiple-choice generated_from_trainer endpoints_compatible region:us
---
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: clinical-bigbird-medqa-usmle-nocontext
  results: []
---

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# clinical-bigbird-medqa-usmle-nocontext

This model is a fine-tuned version of [yikuan8/Clinical-BigBird](https://huggingface.co/yikuan8/Clinical-BigBird) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3863
- Accuracy: 0.2482

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 159  | 1.3860          | 0.2584   |
| No log        | 2.0   | 318  | 1.3859          | 0.2820   |
| No log        | 3.0   | 477  | 1.3863          | 0.2522   |
| 1.3891        | 4.0   | 636  | 1.3863          | 0.2498   |
| 1.3891        | 5.0   | 795  | 1.3863          | 0.2404   |
| 1.3891        | 6.0   | 954  | 1.3863          | 0.2498   |
| 1.3882        | 7.0   | 1113 | 1.3863          | 0.2506   |
| 1.3882        | 8.0   | 1272 | 1.3863          | 0.2467   |
| 1.3882        | 9.0   | 1431 | 1.3863          | 0.2490   |
| 1.3876        | 10.0  | 1590 | 1.3863          | 0.2482   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2
