transformers tf segformer generated_from_keras_callback base_model:nvidia/mit-b0 license:other endpoints_compatible region:us
---
license: other
base_model: nvidia/mit-b0
tags:
- generated_from_keras_callback
model-index:
- name: sf_20240220_v2
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# sf_20240220_v2

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0514
- Validation Loss: 0.0698
- Epoch: 14

## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 0.0006, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 0.1435     | 0.1090          | 0     |
| 0.0923     | 0.0976          | 1     |
| 0.0815     | 0.0951          | 2     |
| 0.0760     | 0.0959          | 3     |
| 0.0735     | 0.0844          | 4     |
| 0.0710     | 0.0824          | 5     |
| 0.0669     | 0.0719          | 6     |
| 0.0628     | 0.0738          | 7     |
| 0.0664     | 0.0801          | 8     |
| 0.0665     | 0.0756          | 9     |
| 0.0612     | 0.0672          | 10    |
| 0.0571     | 0.0703          | 11    |
| 0.0546     | 0.0714          | 12    |
| 0.0553     | 0.0841          | 13    |
| 0.0514     | 0.0698          | 14    |


### Framework versions

- Transformers 4.37.0
- TensorFlow 2.15.0
- Datasets 2.1.0
- Tokenizers 0.15.1
