---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_keras_callback
model-index:
- name: transformers-qa-kaggle-tpu
  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. -->

# transformers-qa-kaggle-tpu

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2278
- Train End Logits Accuracy: 0.9244
- Train Start Logits Accuracy: 0.9207
- Validation Loss: 3.8999
- Validation End Logits Accuracy: 0.4812
- Validation Start Logits Accuracy: 0.4542
- 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': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 122160, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 2.2837     | 0.4519                    | 0.4182                      | 2.1117          | 0.4890                         | 0.4658                           | 0     |
| 1.7361     | 0.5642                    | 0.5326                      | 2.0268          | 0.5035                         | 0.4788                           | 1     |
| 1.4664     | 0.6186                    | 0.5893                      | 2.0023          | 0.5093                         | 0.4833                           | 2     |
| 1.2479     | 0.6661                    | 0.6379                      | 2.1252          | 0.5057                         | 0.4744                           | 3     |
| 1.0596     | 0.7076                    | 0.6832                      | 2.2703          | 0.4975                         | 0.4690                           | 4     |
| 0.8999     | 0.7434                    | 0.7214                      | 2.3834          | 0.4968                         | 0.4714                           | 5     |
| 0.7661     | 0.7760                    | 0.7557                      | 2.5503          | 0.4906                         | 0.4654                           | 6     |
| 0.6520     | 0.8042                    | 0.7892                      | 2.7740          | 0.4922                         | 0.4540                           | 7     |
| 0.5549     | 0.8313                    | 0.8156                      | 3.0625          | 0.4884                         | 0.4607                           | 8     |
| 0.4739     | 0.8512                    | 0.8405                      | 3.1365          | 0.4862                         | 0.4535                           | 9     |
| 0.4072     | 0.8691                    | 0.8620                      | 3.2969          | 0.4830                         | 0.4509                           | 10    |
| 0.3515     | 0.8863                    | 0.8786                      | 3.4301          | 0.4852                         | 0.4530                           | 11    |
| 0.3025     | 0.9010                    | 0.8954                      | 3.5350          | 0.4814                         | 0.4548                           | 12    |
| 0.2646     | 0.9127                    | 0.9083                      | 3.7923          | 0.4832                         | 0.4539                           | 13    |
| 0.2278     | 0.9244                    | 0.9207                      | 3.8999          | 0.4812                         | 0.4542                           | 14    |


### Framework versions

- Transformers 4.31.0.dev0
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3