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---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Sebastian77/distilbert-base-uncased-finetuned-plantl_gob_es
results: []
language:
- es
---
<!-- 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. -->
# Sebastian77/distilbert-base-uncased-finetuned-plantl_gob_es
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.7487
- Train End Logits Accuracy: 0.5839
- Train Start Logits Accuracy: 0.5369
- Validation Loss: 2.0212
- Validation End Logits Accuracy: 0.5396
- Validation Start Logits Accuracy: 0.5058
- Epoch: 2
## 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 5046, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 2.6777 | 0.4400 | 0.4209 | 2.1506 | 0.5098 | 0.4806 | 0 |
| 2.0078 | 0.5336 | 0.4909 | 2.0486 | 0.5289 | 0.4965 | 1 |
| 1.7487 | 0.5839 | 0.5369 | 2.0212 | 0.5396 | 0.5058 | 2 |
### Framework versions
- Transformers 4.27.3
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2 |