
<!-- 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. -->

# model_Projecte_ALC_subtask2

This model is a fine-tuned version of [vinai/bertweet-large](https://huggingface.co/vinai/bertweet-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0379
- Accuracy: 0.6
- F1: 0.5978

## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 9    | 1.5806          | 0.35     | 0.2694 |
| No log        | 2.0   | 18   | 1.5103          | 0.325    | 0.2601 |
| No log        | 3.0   | 27   | 1.3555          | 0.475    | 0.4661 |
| No log        | 4.0   | 36   | 1.3701          | 0.475    | 0.4699 |
| No log        | 5.0   | 45   | 1.3776          | 0.55     | 0.5509 |
| No log        | 6.0   | 54   | 1.3842          | 0.6      | 0.5902 |
| No log        | 7.0   | 63   | 1.4965          | 0.55     | 0.4856 |
| No log        | 8.0   | 72   | 1.6036          | 0.525    | 0.5316 |
| No log        | 9.0   | 81   | 1.7592          | 0.6      | 0.5935 |
| No log        | 10.0  | 90   | 1.9384          | 0.575    | 0.5664 |
| No log        | 11.0  | 99   | 1.8985          | 0.575    | 0.5762 |
| No log        | 12.0  | 108  | 2.0379          | 0.6      | 0.5978 |
| No log        | 13.0  | 117  | 2.3588          | 0.55     | 0.5333 |
| No log        | 14.0  | 126  | 2.1995          | 0.575    | 0.5653 |
| No log        | 15.0  | 135  | 2.4147          | 0.525    | 0.5228 |
| No log        | 16.0  | 144  | 2.5870          | 0.55     | 0.55   |
| No log        | 17.0  | 153  | 2.6592          | 0.55     | 0.5312 |
| No log        | 18.0  | 162  | 2.5286          | 0.55     | 0.55   |
| No log        | 19.0  | 171  | 2.5172          | 0.575    | 0.5758 |
| No log        | 20.0  | 180  | 2.5807          | 0.575    | 0.5758 |
| No log        | 21.0  | 189  | 2.6641          | 0.55     | 0.5330 |
| No log        | 22.0  | 198  | 2.7202          | 0.525    | 0.5141 |
| No log        | 23.0  | 207  | 2.6850          | 0.55     | 0.5457 |
| No log        | 24.0  | 216  | 2.6898          | 0.575    | 0.5741 |
| No log        | 25.0  | 225  | 2.7004          | 0.6      | 0.5968 |


### Framework versions

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

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "model_Projecte_ALC_subtask2", "results": []}]}
transformers pytorch tensorboard roberta text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

model\_Projecte\_ALC\_subtask2
==============================


This model is a fine-tuned version of vinai/bertweet-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.0379
* Accuracy: 0.6
* F1: 0.5978


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: 7e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 25.0


### 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: 7e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 25.0 ### Training results ### Framework versions


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


The following hyperparameters were used during training:


* learning\_rate: 7e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 25.0 ### Training results ### Framework versions


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