|
--- |
|
license: mit |
|
tags: |
|
- generated_from_keras_callback |
|
model-index: |
|
- name: xmelus/invoices-roberta-large |
|
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. --> |
|
|
|
# xmelus/invoices-roberta-large |
|
|
|
This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on [dataset](https://huggingface.co/datasets/fimu-docproc-research/lm_invoices) . |
|
It achieves the following results on the evaluation set: |
|
- Train Loss: 2.2317 |
|
- Train Accuracy: 0.0883 |
|
- Validation Loss: 2.1699 |
|
- Validation Accuracy: 0.0899 |
|
- Finished epochs: 13 |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 754, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} |
|
- training_precision: mixed_float16 |
|
|
|
### Training results |
|
|
|
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
|
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
|
|11.4516 | 0.0165 | 4.5115 | 0.0501 | 0 | |
|
| 3.6182 | 0.0628 | 2.8398 | 0.0752 | 1 | |
|
| 2.2317 | 0.0883 | 2.1699 | 0.0899 | 2 | |
|
| 1.9700 | 0.0942 | 2.5529 | 0.0831 | 3 | |
|
| 1.9714 | 0.0941 | 2.4961 | 0.0843 | 4 | |
|
| 1.9682 | 0.0940 | 2.5089 | 0.0839 | 5 | |
|
| 1.9546 | 0.0944 | 2.5029 | 0.0841 | 6 | |
|
| 1.9808 | 0.0939 | 2.5140 | 0.0838 | 7 | |
|
| 1.9728 | 0.0937 | 2.5212 | 0.0833 | 8 | |
|
| 1.9655 | 0.0941 | 2.5575 | 0.0838 | 9 | |
|
| 1.9708 | 0.0935 | 2.5419 | 0.0833 | 10 | |
|
| 1.9693 | 0.0940 | 2.5304 | 0.0836 | 11 | |
|
| 1.9614 | 0.0941 | 2.5176 | 0.0835 | 12 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.2 |
|
- TensorFlow 2.8.2 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
