license: other | |
tags: | |
- generated_from_trainer | |
model-index: | |
- name: tumore_test | |
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. --> | |
# tumore_test | |
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset. | |
It achieves the following results on the evaluation set: | |
- eval_loss: 0.0 | |
- eval_mean_iou: nan | |
- eval_mean_accuracy: nan | |
- eval_overall_accuracy: nan | |
- eval_per_category_iou: [nan] | |
- eval_per_category_accuracy: [nan] | |
- eval_runtime: 338.6408 | |
- eval_samples_per_second: 1.161 | |
- eval_steps_per_second: 0.582 | |
- epoch: 1.27 | |
- step: 2000 | |
## 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: 6e-05 | |
- train_batch_size: 2 | |
- eval_batch_size: 2 | |
- seed: 42 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- num_epochs: 2 | |
### Framework versions | |
- Transformers 4.26.1 | |
- Pytorch 1.13.0 | |
- Datasets 2.10.1 | |
- Tokenizers 0.13.2 | |