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---
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: 0.2138
- Train End Logits Accuracy: 0.9272
- Train Start Logits Accuracy: 0.9265
- Validation Loss: 4.0782
- Validation End Logits Accuracy: 0.4815
- Validation Start Logits Accuracy: 0.4488
- 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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 2.2397 | 0.4602 | 0.4288 | 2.0601 | 0.4944 | 0.4670 | 0 |
| 1.7080 | 0.5695 | 0.5404 | 2.0597 | 0.5098 | 0.4782 | 1 |
| 1.4423 | 0.6244 | 0.5975 | 2.0398 | 0.5124 | 0.4779 | 2 |
| 1.2221 | 0.6718 | 0.6455 | 2.1899 | 0.5121 | 0.4832 | 3 |
| 1.0321 | 0.7138 | 0.6920 | 2.2860 | 0.5067 | 0.4742 | 4 |
| 0.8740 | 0.7502 | 0.7307 | 2.4042 | 0.4981 | 0.4677 | 5 |
| 0.7420 | 0.7809 | 0.7666 | 2.6543 | 0.4954 | 0.4595 | 6 |
| 0.6254 | 0.8107 | 0.7988 | 2.7405 | 0.4938 | 0.4607 | 7 |
| 0.5325 | 0.8337 | 0.8255 | 3.0218 | 0.4911 | 0.4613 | 8 |
| 0.4537 | 0.8550 | 0.8491 | 3.1804 | 0.4917 | 0.4550 | 9 |
| 0.3860 | 0.8751 | 0.8707 | 3.4298 | 0.4880 | 0.4524 | 10 |
| 0.3284 | 0.8914 | 0.8890 | 3.5952 | 0.4826 | 0.4480 | 11 |
| 0.2844 | 0.9053 | 0.9033 | 3.6105 | 0.4856 | 0.4510 | 12 |
| 0.2462 | 0.9176 | 0.9151 | 3.8751 | 0.4785 | 0.4504 | 13 |
| 0.2138 | 0.9272 | 0.9265 | 4.0782 | 0.4815 | 0.4488 | 14 |
### Framework versions
- Transformers 4.31.0.dev0
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3
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