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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: resnet-50_finetuned
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. -->
# resnet-50_finetuned
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7209
- Precision: 0.3702
- Recall: 0.5
- F1: 0.4254
- Accuracy: 0.7404
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 46 | 0.6599 | 0.3702 | 0.5 | 0.4254 | 0.7404 |
| No log | 2.0 | 92 | 0.6725 | 0.3702 | 0.5 | 0.4254 | 0.7404 |
| No log | 3.0 | 138 | nan | 0.8714 | 0.5062 | 0.4384 | 0.7436 |
| No log | 4.0 | 184 | nan | 0.8714 | 0.5062 | 0.4384 | 0.7436 |
| No log | 5.0 | 230 | nan | 0.8714 | 0.5062 | 0.4384 | 0.7436 |
| No log | 6.0 | 276 | nan | 0.8714 | 0.5062 | 0.4384 | 0.7436 |
| No log | 7.0 | 322 | nan | 0.8714 | 0.5062 | 0.4384 | 0.7436 |
| No log | 8.0 | 368 | nan | 0.8714 | 0.5062 | 0.4384 | 0.7436 |
| No log | 9.0 | 414 | nan | 0.8714 | 0.5062 | 0.4384 | 0.7436 |
| No log | 10.0 | 460 | 0.7209 | 0.3702 | 0.5 | 0.4254 | 0.7404 |
### Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
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