File size: 2,825 Bytes
06ec5fa 7a4f1c8 06ec5fa 7a4f1c8 06ec5fa 7a4f1c8 06ec5fa |
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 |
---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert_seed33_1311
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. -->
# multibert_seed33_1311
This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4745
- Precisions: 0.8770
- Recall: 0.8049
- F-measure: 0.8343
- Accuracy: 0.9364
## 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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 34
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4458 | 1.0 | 236 | 0.2719 | 0.8870 | 0.7002 | 0.7379 | 0.9144 |
| 0.2302 | 2.0 | 472 | 0.2497 | 0.8728 | 0.7439 | 0.7647 | 0.9209 |
| 0.139 | 3.0 | 708 | 0.2849 | 0.8797 | 0.7900 | 0.8231 | 0.9340 |
| 0.0881 | 4.0 | 944 | 0.3292 | 0.8694 | 0.7757 | 0.8140 | 0.9296 |
| 0.0539 | 5.0 | 1180 | 0.3674 | 0.8488 | 0.7775 | 0.8061 | 0.9272 |
| 0.0382 | 6.0 | 1416 | 0.3497 | 0.8482 | 0.8083 | 0.8263 | 0.9356 |
| 0.0266 | 7.0 | 1652 | 0.3809 | 0.8435 | 0.8162 | 0.8281 | 0.9366 |
| 0.0187 | 8.0 | 1888 | 0.4222 | 0.8522 | 0.7840 | 0.8096 | 0.9303 |
| 0.0133 | 9.0 | 2124 | 0.4423 | 0.8646 | 0.7878 | 0.8176 | 0.9356 |
| 0.0085 | 10.0 | 2360 | 0.4632 | 0.8538 | 0.8005 | 0.8221 | 0.9342 |
| 0.007 | 11.0 | 2596 | 0.4638 | 0.8632 | 0.8026 | 0.8281 | 0.9342 |
| 0.0031 | 12.0 | 2832 | 0.4679 | 0.8720 | 0.8037 | 0.8303 | 0.9361 |
| 0.0023 | 13.0 | 3068 | 0.4712 | 0.8644 | 0.8098 | 0.8327 | 0.9366 |
| 0.0018 | 14.0 | 3304 | 0.4745 | 0.8770 | 0.8049 | 0.8343 | 0.9364 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
|