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# bert-xxl-incl

This model is a fine-tuned version of [dbmdz/bert-base-italian-xxl-uncased](https://huggingface.co/dbmdz/bert-base-italian-xxl-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0005
- Acc: 1.0
- F1 Macro: 1.0
- F1 Weight: 1.0

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Acc    | F1 Macro | F1 Weight |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|
| 0.6075        | 2.5   | 20   | 0.2080          | 0.9853 | 0.9851   | 0.9853    |
| 0.0448        | 5.0   | 40   | 0.0012          | 1.0    | 1.0      | 1.0       |
| 0.001         | 7.5   | 60   | 0.0005          | 1.0    | 1.0      | 1.0       |
| 0.0007        | 10.0  | 80   | 0.0005          | 1.0    | 1.0      | 1.0       |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-xxl-incl", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

bert-xxl-incl
=============


This model is a fine-tuned version of dbmdz/bert-base-italian-xxl-uncased on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0005
* Acc: 1.0
* F1 Macro: 1.0
* F1 Weight: 1.0


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: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 20
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 20
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 20
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 20
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3