|
--- |
|
license: apache-2.0 |
|
base_model: distilbert-base-uncased |
|
tags: |
|
- generated_from_keras_callback |
|
model-index: |
|
- name: edyfjm07/distilbert-base-uncased-QA3-finetuned-squad-es |
|
results: [] |
|
datasets: |
|
- edyfjm07/squad_indicaciones_es |
|
language: |
|
- es |
|
metrics: |
|
- rouge |
|
- recall |
|
- accuracy |
|
- f1 |
|
--- |
|
|
|
<!-- 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-QA3-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: 5.9545 |
|
- Train End Logits Accuracy: 0.0032 |
|
- Train Start Logits Accuracy: 0.0 |
|
- Validation Loss: 5.9506 |
|
- Validation End Logits Accuracy: 0.0 |
|
- Validation Start Logits Accuracy: 0.0063 |
|
- Epoch: 40 |
|
|
|
## 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': 0.001, 'decay_steps': 2419, '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 | |
|
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:| |
|
| 4.7467 | 0.1006 | 0.0561 | 5.8046 | 0.0157 | 0.0878 | 0 | |
|
| 4.8045 | 0.0148 | 0.0138 | 5.2042 | 0.0094 | 0.0094 | 1 | |
|
| 5.9402 | 0.0032 | 0.0053 | 5.9506 | 0.0031 | 0.0063 | 2 | |
|
| 5.9626 | 0.0021 | 0.0021 | 5.9506 | 0.0031 | 0.0031 | 3 | |
|
| 5.9599 | 0.0042 | 0.0 | 5.9506 | 0.0 | 0.0 | 4 | |
|
| 5.9718 | 0.0 | 0.0011 | 5.9506 | 0.0 | 0.0031 | 5 | |
|
| 5.9587 | 0.0021 | 0.0064 | 5.9506 | 0.0031 | 0.0031 | 6 | |
|
| 5.9657 | 0.0064 | 0.0032 | 5.9506 | 0.0031 | 0.0188 | 7 | |
|
| 5.9617 | 0.0021 | 0.0032 | 5.9506 | 0.0031 | 0.0063 | 8 | |
|
| 5.9596 | 0.0021 | 0.0032 | 5.9506 | 0.0 | 0.0031 | 9 | |
|
| 5.9648 | 0.0021 | 0.0021 | 5.9506 | 0.0094 | 0.0063 | 10 | |
|
| 5.9608 | 0.0021 | 0.0032 | 5.9506 | 0.0125 | 0.0094 | 11 | |
|
| 5.9567 | 0.0021 | 0.0053 | 5.9506 | 0.0063 | 0.0 | 12 | |
|
| 5.9625 | 0.0011 | 0.0011 | 5.9506 | 0.0 | 0.0 | 13 | |
|
| 5.9640 | 0.0 | 0.0011 | 5.9506 | 0.0031 | 0.0 | 14 | |
|
| 5.9606 | 0.0011 | 0.0 | 5.9506 | 0.0063 | 0.0063 | 15 | |
|
| 5.9622 | 0.0032 | 0.0053 | 5.9506 | 0.0094 | 0.0063 | 16 | |
|
| 5.9600 | 0.0011 | 0.0021 | 5.9506 | 0.0 | 0.0063 | 17 | |
|
| 5.9579 | 0.0011 | 0.0011 | 5.9506 | 0.0063 | 0.0094 | 18 | |
|
| 5.9598 | 0.0032 | 0.0053 | 5.9506 | 0.0031 | 0.0 | 19 | |
|
| 5.9589 | 0.0021 | 0.0032 | 5.9506 | 0.0063 | 0.0031 | 20 | |
|
| 5.9566 | 0.0032 | 0.0021 | 5.9506 | 0.0 | 0.0 | 21 | |
|
| 5.9536 | 0.0011 | 0.0053 | 5.9506 | 0.0 | 0.0 | 22 | |
|
| 5.9592 | 0.0021 | 0.0021 | 5.9506 | 0.0031 | 0.0031 | 23 | |
|
| 5.9548 | 0.0032 | 0.0042 | 5.9506 | 0.0 | 0.0 | 24 | |
|
| 5.9569 | 0.0 | 0.0021 | 5.9506 | 0.0 | 0.0 | 25 | |
|
| 5.9640 | 0.0032 | 0.0011 | 5.9506 | 0.0031 | 0.0031 | 26 | |
|
| 5.9497 | 0.0011 | 0.0011 | 5.9506 | 0.0 | 0.0031 | 27 | |
|
| 5.9558 | 0.0 | 0.0053 | 5.9506 | 0.0063 | 0.0031 | 28 | |
|
| 5.9563 | 0.0021 | 0.0032 | 5.9506 | 0.0063 | 0.0063 | 29 | |
|
| 5.9585 | 0.0032 | 0.0032 | 5.9506 | 0.0 | 0.0094 | 30 | |
|
| 5.9569 | 0.0011 | 0.0021 | 5.9506 | 0.0094 | 0.0063 | 31 | |
|
| 5.9580 | 0.0011 | 0.0021 | 5.9506 | 0.0063 | 0.0 | 32 | |
|
| 5.9532 | 0.0032 | 0.0011 | 5.9506 | 0.0 | 0.0063 | 33 | |
|
| 5.9523 | 0.0021 | 0.0032 | 5.9506 | 0.0 | 0.0 | 34 | |
|
| 5.9552 | 0.0042 | 0.0011 | 5.9506 | 0.0 | 0.0 | 35 | |
|
| 5.9538 | 0.0021 | 0.0032 | 5.9506 | 0.0 | 0.0 | 36 | |
|
| 5.9538 | 0.0032 | 0.0032 | 5.9506 | 0.0031 | 0.0063 | 37 | |
|
| 5.9567 | 0.0011 | 0.0021 | 5.9506 | 0.0063 | 0.0031 | 38 | |
|
| 5.9570 | 0.0053 | 0.0032 | 5.9506 | 0.0 | 0.0031 | 39 | |
|
| 5.9545 | 0.0032 | 0.0 | 5.9506 | 0.0 | 0.0063 | 40 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- TensorFlow 2.15.0 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
