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---
library_name: transformers
license: apache-2.0
base_model: barghavani/Cheese_xray
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Cheese_X_ray
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. -->
# Cheese_X_ray
This model is a fine-tuned version of [barghavani/Cheese_xray](https://huggingface.co/barghavani/Cheese_xray) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1890
- Accuracy: 0.9381
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.5579 | 0.9882 | 63 | 0.5524 | 0.7062 |
| 0.4491 | 1.9922 | 127 | 0.4218 | 0.7062 |
| 0.3646 | 2.9961 | 191 | 0.3928 | 0.7440 |
| 0.3419 | 4.0 | 255 | 0.3827 | 0.8110 |
| 0.3546 | 4.9882 | 318 | 0.3530 | 0.8608 |
| 0.3745 | 5.9922 | 382 | 0.3298 | 0.8814 |
| 0.3323 | 6.9961 | 446 | 0.3022 | 0.8952 |
| 0.3125 | 8.0 | 510 | 0.2750 | 0.9089 |
| 0.2663 | 8.9882 | 573 | 0.2648 | 0.8883 |
| 0.2672 | 9.9922 | 637 | 0.2476 | 0.9038 |
| 0.2492 | 10.9961 | 701 | 0.2354 | 0.9278 |
| 0.2297 | 12.0 | 765 | 0.2272 | 0.9175 |
| 0.1915 | 12.9882 | 828 | 0.2126 | 0.9107 |
| 0.2071 | 13.9922 | 892 | 0.2006 | 0.9227 |
| 0.2251 | 14.9961 | 956 | 0.1806 | 0.9244 |
| 0.1979 | 16.0 | 1020 | 0.1900 | 0.9347 |
| 0.1969 | 16.9882 | 1083 | 0.2081 | 0.9192 |
| 0.2 | 17.9922 | 1147 | 0.2037 | 0.9175 |
| 0.2082 | 18.9961 | 1211 | 0.2108 | 0.9175 |
| 0.1838 | 19.7647 | 1260 | 0.1688 | 0.9330 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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