File size: 2,195 Bytes
229a5b7 ebab994 229a5b7 ebab994 229a5b7 e813de0 28b726d 36e1388 ebab994 229a5b7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
---
license: mit
base_model: badokorach/mobilebert-uncased-finetuned-agic-060124
tags:
- generated_from_keras_callback
model-index:
- name: badokorach/minilm-uncased-squad2-agric-17024
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. -->
# badokorach/minilm-uncased-squad2-agric-17024
This model is a fine-tuned version of [badokorach/mobilebert-uncased-finetuned-agic-060124](https://huggingface.co/badokorach/mobilebert-uncased-finetuned-agic-060124) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0258
- Validation Loss: 0.0
- Epoch: 4
## 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: {'inner_optimizer': {'module': 'keras.optimizers', 'class_name': 'Adam', 'config': {'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': {'module': None, 'class_name': 'CustomLearningRateScheduler', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 2736, 'warmup_steps': 304, 'end_learning_rate': 1e-05}, 'registered_name': 'CustomLearningRateScheduler'}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}, 'registered_name': None}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 4.9158 | 0.0 | 0 |
| 0.2937 | 0.0 | 1 |
| 0.0747 | 0.0 | 2 |
| 0.0398 | 0.0 | 3 |
| 0.0258 | 0.0 | 4 |
### Framework versions
- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.17.0
- Tokenizers 0.15.2
|