---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
model-index:
- name: bert-base-multilingual-uncased-finetuned-hp
  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. -->

# bert-base-multilingual-uncased-finetuned-hp

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4747

## 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: 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.6826        | 1.0   | 66   | 2.4979          |
| 2.4316        | 2.0   | 132  | 2.2737          |
| 2.2563        | 3.0   | 198  | 2.1285          |
| 2.1158        | 4.0   | 264  | 2.0855          |
| 2.0196        | 5.0   | 330  | 1.9913          |
| 1.9651        | 6.0   | 396  | 1.9124          |
| 1.8956        | 7.0   | 462  | 1.9461          |
| 1.856         | 8.0   | 528  | 1.9519          |
| 1.8146        | 9.0   | 594  | 1.8063          |
| 1.7675        | 10.0  | 660  | 1.8229          |
| 1.7473        | 11.0  | 726  | 1.8271          |
| 1.7069        | 12.0  | 792  | 1.8147          |
| 1.678         | 13.0  | 858  | 1.8209          |
| 1.6291        | 14.0  | 924  | 1.7894          |
| 1.6251        | 15.0  | 990  | 1.7851          |
| 1.5939        | 16.0  | 1056 | 1.7237          |
| 1.5635        | 17.0  | 1122 | 1.7627          |
| 1.5088        | 18.0  | 1188 | 1.7392          |
| 1.5136        | 19.0  | 1254 | 1.6703          |
| 1.4782        | 20.0  | 1320 | 1.6922          |
| 1.4714        | 21.0  | 1386 | 1.6810          |
| 1.4451        | 22.0  | 1452 | 1.6318          |
| 1.4399        | 23.0  | 1518 | 1.6579          |
| 1.4262        | 24.0  | 1584 | 1.6303          |
| 1.3736        | 25.0  | 1650 | 1.6777          |
| 1.3896        | 26.0  | 1716 | 1.6887          |
| 1.3508        | 27.0  | 1782 | 1.6420          |
| 1.3939        | 28.0  | 1848 | 1.6026          |
| 1.3334        | 29.0  | 1914 | 1.6820          |
| 1.3169        | 30.0  | 1980 | 1.6018          |
| 1.2857        | 31.0  | 2046 | 1.6437          |
| 1.3152        | 32.0  | 2112 | 1.5975          |
| 1.2835        | 33.0  | 2178 | 1.6155          |
| 1.2388        | 34.0  | 2244 | 1.6033          |
| 1.2591        | 35.0  | 2310 | 1.6100          |
| 1.246         | 36.0  | 2376 | 1.5424          |
| 1.2196        | 37.0  | 2442 | 1.6082          |
| 1.2341        | 38.0  | 2508 | 1.4954          |
| 1.196         | 39.0  | 2574 | 1.5132          |
| 1.2025        | 40.0  | 2640 | 1.5710          |
| 1.1778        | 41.0  | 2706 | 1.5356          |
| 1.1645        | 42.0  | 2772 | 1.5545          |
| 1.1729        | 43.0  | 2838 | 1.4637          |
| 1.1542        | 44.0  | 2904 | 1.5700          |
| 1.1505        | 45.0  | 2970 | 1.5840          |
| 1.1224        | 46.0  | 3036 | 1.5451          |
| 1.118         | 47.0  | 3102 | 1.6250          |
| 1.0997        | 48.0  | 3168 | 1.4816          |
| 1.109         | 49.0  | 3234 | 1.5641          |
| 1.1243        | 50.0  | 3300 | 1.5099          |
| 1.1159        | 51.0  | 3366 | 1.5584          |
| 1.0955        | 52.0  | 3432 | 1.5589          |
| 1.0557        | 53.0  | 3498 | 1.5601          |
| 1.0685        | 54.0  | 3564 | 1.5211          |
| 1.0674        | 55.0  | 3630 | 1.5651          |
| 1.0625        | 56.0  | 3696 | 1.5918          |
| 1.0403        | 57.0  | 3762 | 1.5817          |
| 1.0197        | 58.0  | 3828 | 1.4936          |
| 1.031         | 59.0  | 3894 | 1.5860          |
| 1.0364        | 60.0  | 3960 | 1.5774          |
| 1.0375        | 61.0  | 4026 | 1.5358          |
| 1.0127        | 62.0  | 4092 | 1.5451          |
| 0.9982        | 63.0  | 4158 | 1.5271          |
| 0.9949        | 64.0  | 4224 | 1.5242          |
| 0.9962        | 65.0  | 4290 | 1.5564          |
| 1.0084        | 66.0  | 4356 | 1.5668          |
| 1.0076        | 67.0  | 4422 | 1.5867          |
| 0.9892        | 68.0  | 4488 | 1.5238          |
| 0.9889        | 69.0  | 4554 | 1.5097          |
| 0.9932        | 70.0  | 4620 | 1.5491          |
| 0.9815        | 71.0  | 4686 | 1.4237          |
| 0.9777        | 72.0  | 4752 | 1.5569          |
| 0.9525        | 73.0  | 4818 | 1.5103          |
| 0.9607        | 74.0  | 4884 | 1.5665          |
| 0.9488        | 75.0  | 4950 | 1.5910          |
| 0.9492        | 76.0  | 5016 | 1.5779          |
| 0.9667        | 77.0  | 5082 | 1.5581          |
| 0.9495        | 78.0  | 5148 | 1.4898          |
| 0.9457        | 79.0  | 5214 | 1.5638          |
| 0.9511        | 80.0  | 5280 | 1.5825          |
| 0.9173        | 81.0  | 5346 | 1.5565          |
| 0.9209        | 82.0  | 5412 | 1.5550          |
| 0.9446        | 83.0  | 5478 | 1.5431          |
| 0.9479        | 84.0  | 5544 | 1.4988          |
| 0.8999        | 85.0  | 5610 | 1.5311          |
| 0.9096        | 86.0  | 5676 | 1.5187          |
| 0.9044        | 87.0  | 5742 | 1.4801          |
| 0.8849        | 88.0  | 5808 | 1.5176          |
| 0.9006        | 89.0  | 5874 | 1.5871          |
| 0.9038        | 90.0  | 5940 | 1.4757          |
| 0.9026        | 91.0  | 6006 | 1.5138          |
| 0.8935        | 92.0  | 6072 | 1.6166          |
| 0.8812        | 93.0  | 6138 | 1.5561          |
| 0.8725        | 94.0  | 6204 | 1.5315          |
| 0.8941        | 95.0  | 6270 | 1.5468          |
| 0.9013        | 96.0  | 6336 | 1.6091          |
| 0.9232        | 97.0  | 6402 | 1.5199          |
| 0.8891        | 98.0  | 6468 | 1.5210          |
| 0.8956        | 99.0  | 6534 | 1.4859          |
| 0.8876        | 100.0 | 6600 | 1.4610          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1