File size: 1,996 Bytes
53056cd |
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 |
---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: model_all
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# model_all
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4240
- Accuracy: 0.7937
- F1: 0.7937
- Precision: 0.7937
- Recall: 0.7937
## 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:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.9958 | 1.0 | 753 | 1.0623 | 0.6951 | 0.6951 | 0.6951 | 0.6951 |
| 0.3471 | 2.0 | 1506 | 1.0435 | 0.7579 | 0.7579 | 0.7579 | 0.7579 |
| 0.1329 | 3.0 | 2259 | 1.1884 | 0.7844 | 0.7844 | 0.7844 | 0.7844 |
| 0.0612 | 4.0 | 3012 | 1.3113 | 0.7851 | 0.7851 | 0.7851 | 0.7851 |
| 0.0263 | 5.0 | 3765 | 1.4240 | 0.7937 | 0.7937 | 0.7937 | 0.7937 |
| 0.0237 | 6.0 | 4518 | 1.5578 | 0.7824 | 0.7824 | 0.7824 | 0.7824 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
|