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: segformer_400samples_13of20epochs_4batch
  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. -->

# segformer_400samples_13of20epochs_4batch

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: 0.1547
- Validation Loss: 0.2291
- Epoch: 12

## 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': 6e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 0.4764     | 0.2749          | 0     |
| 0.3092     | 0.3437          | 1     |
| 0.2745     | 0.3007          | 2     |
| 0.2509     | 0.2527          | 3     |
| 0.2402     | 0.2469          | 4     |
| 0.2357     | 0.1991          | 5     |
| 0.2091     | 0.1949          | 6     |
| 0.2095     | 0.1833          | 7     |
| 0.1968     | 0.1662          | 8     |
| 0.1612     | 0.1446          | 9     |
| 0.1680     | 0.1658          | 10    |
| 0.1486     | 0.2235          | 11    |
| 0.1547     | 0.2291          | 12    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Tokenizers 0.15.2
