---
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