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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: nystromformer-4096-medqa-usmle-MiniLM-IR-cs
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. -->
# nystromformer-4096-medqa-usmle-MiniLM-IR-cs
This model is a fine-tuned version of [GBaker/nystromformer-4096-medqa-usmle-MiniLM-IR-cs](https://huggingface.co/GBaker/nystromformer-4096-medqa-usmle-MiniLM-IR-cs) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8436
- Accuracy: 0.2812
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- 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 | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| No log | 0.99 | 79 | 0.2372 | 1.3863 |
| No log | 1.99 | 158 | 0.2655 | 1.3861 |
| No log | 2.99 | 237 | 0.2545 | 1.3859 |
| No log | 3.99 | 316 | 0.2765 | 1.3837 |
| No log | 4.99 | 395 | 0.2820 | 1.3876 |
| No log | 5.99 | 474 | 1.3819 | 0.2639 |
| 1.3342 | 6.99 | 553 | 1.4875 | 0.2694 |
| 1.3342 | 7.99 | 632 | 1.6126 | 0.2718 |
| 1.3342 | 8.99 | 711 | 1.7637 | 0.2804 |
| 1.3342 | 9.99 | 790 | 1.8436 | 0.2812 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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