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# nli_mbert

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:
- Loss: 1.6569
- Accuracy: 0.7419
- Precision: 0.7419
- Recall: 0.7419
- F1 Score: 0.7426

## 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: 3e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 101
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 1.403         | 1.0   | 10330 | 1.3860          | 0.7128   | 0.7128    | 0.7128 | 0.7142   |
| 1.3213        | 2.0   | 20660 | 1.3367          | 0.7365   | 0.7365    | 0.7365 | 0.7371   |
| 1.1611        | 3.0   | 30990 | 1.4699          | 0.7396   | 0.7396    | 0.7396 | 0.7406   |
| 1.0222        | 4.0   | 41320 | 1.6050          | 0.7374   | 0.7374    | 0.7374 | 0.7383   |
| 0.9008        | 5.0   | 51650 | 1.6569          | 0.7419   | 0.7419    | 0.7419 | 0.7426   |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall"], "model-index": [{"name": "nli_mbert", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

nli\_mbert
==========


This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.6569
* Accuracy: 0.7419
* Precision: 0.7419
* Recall: 0.7419
* F1 Score: 0.7426


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: 3e-06
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 101
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-06
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 101
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-06
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 101
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3