File size: 2,831 Bytes
1f0c859 725c50f 1f0c859 |
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: MultiBERTBestModelOct11
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. -->
# multibert0510_lrate7.5b16
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: 0.5930
- Precisions: 0.8750
- Recall: 0.8217
- F-measure: 0.8450
- Accuracy: 0.9133
## 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: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6022 | 1.0 | 236 | 0.4256 | 0.8484 | 0.6548 | 0.6844 | 0.8642 |
| 0.3396 | 2.0 | 472 | 0.3851 | 0.8046 | 0.7225 | 0.7312 | 0.8773 |
| 0.2116 | 3.0 | 708 | 0.3670 | 0.8311 | 0.7347 | 0.7560 | 0.8947 |
| 0.148 | 4.0 | 944 | 0.4016 | 0.8827 | 0.7716 | 0.8081 | 0.9021 |
| 0.0959 | 5.0 | 1180 | 0.4409 | 0.8338 | 0.8054 | 0.8166 | 0.8998 |
| 0.0809 | 6.0 | 1416 | 0.4964 | 0.8678 | 0.7356 | 0.7799 | 0.8980 |
| 0.056 | 7.0 | 1652 | 0.4894 | 0.8451 | 0.7520 | 0.7855 | 0.8931 |
| 0.038 | 8.0 | 1888 | 0.5008 | 0.8697 | 0.8024 | 0.8301 | 0.9104 |
| 0.031 | 9.0 | 2124 | 0.4813 | 0.8561 | 0.8172 | 0.8335 | 0.9122 |
| 0.02 | 10.0 | 2360 | 0.5857 | 0.8831 | 0.7946 | 0.8305 | 0.9115 |
| 0.0129 | 11.0 | 2596 | 0.5622 | 0.8667 | 0.8039 | 0.8308 | 0.9098 |
| 0.0113 | 12.0 | 2832 | 0.5861 | 0.8746 | 0.8015 | 0.8324 | 0.9104 |
| 0.0065 | 13.0 | 3068 | 0.5964 | 0.8752 | 0.8204 | 0.8443 | 0.9128 |
| 0.004 | 14.0 | 3304 | 0.5930 | 0.8750 | 0.8217 | 0.8450 | 0.9133 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
|