File size: 3,779 Bytes
351bb53 eb3da89 351bb53 10efcbc 1f83eb1 10efcbc 85fe5fe 10efcbc 351bb53 be4ee71 351bb53 be4ee71 1f4439e a1284b4 cc4881e 3a73c2d 4a640c2 1a5e73b a45ecd1 ff9e83a 93c0288 eb893d4 4864b0f 1c301c2 58be434 faa52ed 635cca1 d65281b 85fe5fe 1f83eb1 10efcbc 351bb53 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_keras_callback
model-index:
- name: SIA86/bert-cased-text-classification
results: []
widget:
- text: "Не могу отправить письмо с электронной почты."
example_title: "Почта"
- text: "Прошу изготовить пропуск новому сотруднику."
example_title: "Пропуск"
- text: "Прошу установить AutoCad на мой компьютер"
example_title: "Программы"
---
<!-- 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. -->
# SIA86/bert-cased-text-classification
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0719
- Train Accuracy: 0.9772
- Validation Loss: 0.8075
- Validation Accuracy: 0.8485
- Epoch: 19
## 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 2320, 'end_learning_rate': 0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 2.8423 | 0.2313 | 2.5340 | 0.3593 | 0 |
| 2.4502 | 0.3181 | 2.3051 | 0.3333 | 1 |
| 2.2064 | 0.3648 | 1.9143 | 0.4416 | 2 |
| 1.6431 | 0.5494 | 1.5876 | 0.5411 | 3 |
| 1.1282 | 0.6960 | 1.4404 | 0.6190 | 4 |
| 0.8128 | 0.7861 | 1.0982 | 0.7143 | 5 |
| 0.6016 | 0.8534 | 1.0513 | 0.7532 | 6 |
| 0.4495 | 0.8947 | 0.9108 | 0.7879 | 7 |
| 0.2991 | 0.9414 | 0.8437 | 0.8182 | 8 |
| 0.2068 | 0.9609 | 0.7936 | 0.8182 | 9 |
| 0.1594 | 0.9729 | 0.8264 | 0.8182 | 10 |
| 0.1364 | 0.9707 | 0.7984 | 0.8312 | 11 |
| 0.1217 | 0.9707 | 0.7948 | 0.8268 | 12 |
| 0.1053 | 0.9729 | 0.7847 | 0.8398 | 13 |
| 0.0968 | 0.9729 | 0.7850 | 0.8398 | 14 |
| 0.0879 | 0.9739 | 0.7976 | 0.8442 | 15 |
| 0.0821 | 0.9718 | 0.8005 | 0.8442 | 16 |
| 0.0770 | 0.9750 | 0.7967 | 0.8485 | 17 |
| 0.0772 | 0.9772 | 0.8043 | 0.8485 | 18 |
| 0.0719 | 0.9772 | 0.8075 | 0.8485 | 19 |
### Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.1
- Tokenizers 0.13.3
|