---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: edyfjm07/distilbert-base-uncased-QA1-finetuned-squad-es
  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. -->

# edyfjm07/distilbert-base-uncased-QA1-finetuned-squad-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: 0.5471
- Train End Logits Accuracy: 0.8125
- Train Start Logits Accuracy: 0.8244
- Validation Loss: 0.9933
- Validation End Logits Accuracy: 0.7398
- Validation Start Logits Accuracy: 0.7774
- 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 1479, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 5.1787     | 0.0571                    | 0.0496                      | 4.3181          | 0.1724                         | 0.1818                           | 0     |
| 3.6307     | 0.25                      | 0.1810                      | 2.8944          | 0.3793                         | 0.2476                           | 1     |
| 2.5094     | 0.3998                    | 0.3147                      | 2.1436          | 0.4514                         | 0.3793                           | 2     |
| 1.9078     | 0.4871                    | 0.4397                      | 1.7322          | 0.5204                         | 0.5705                           | 3     |
| 1.5135     | 0.5593                    | 0.5700                      | 1.4332          | 0.6050                         | 0.6238                           | 4     |
| 1.2802     | 0.5927                    | 0.6013                      | 1.3274          | 0.6270                         | 0.6364                           | 5     |
| 1.1079     | 0.6595                    | 0.6455                      | 1.2126          | 0.6520                         | 0.6865                           | 6     |
| 0.9827     | 0.6843                    | 0.7069                      | 1.1469          | 0.7116                         | 0.7116                           | 7     |
| 0.8810     | 0.7306                    | 0.7371                      | 1.0859          | 0.7116                         | 0.7053                           | 8     |
| 0.8194     | 0.7349                    | 0.7446                      | 1.0339          | 0.7429                         | 0.7492                           | 9     |
| 0.7245     | 0.7403                    | 0.7877                      | 1.0371          | 0.7304                         | 0.7398                           | 10    |
| 0.6827     | 0.7683                    | 0.7856                      | 1.0185          | 0.7492                         | 0.7461                           | 11    |
| 0.6421     | 0.7866                    | 0.8071                      | 1.0298          | 0.7492                         | 0.7555                           | 12    |
| 0.5949     | 0.8006                    | 0.8050                      | 0.9877          | 0.7586                         | 0.7774                           | 13    |
| 0.5471     | 0.8125                    | 0.8244                      | 0.9933          | 0.7398                         | 0.7774                           | 14    |


### Framework versions

- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1