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# model_Projecte_ALC_subtask3

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: 1.1149
- Accuracy: 0.7857
- F1: 0.7820

## 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   | 7    | 1.3390          | 0.375    | 0.2958 |
| No log        | 2.0   | 14   | 1.2599          | 0.3929   | 0.3281 |
| No log        | 3.0   | 21   | 1.1885          | 0.375    | 0.3815 |
| No log        | 4.0   | 28   | 1.0292          | 0.5179   | 0.4835 |
| No log        | 5.0   | 35   | 0.7229          | 0.75     | 0.7359 |
| No log        | 6.0   | 42   | 0.8717          | 0.6964   | 0.6843 |
| No log        | 7.0   | 49   | 0.8324          | 0.6964   | 0.6894 |
| No log        | 8.0   | 56   | 0.8172          | 0.7143   | 0.7094 |
| No log        | 9.0   | 63   | 0.7527          | 0.7679   | 0.7663 |
| No log        | 10.0  | 70   | 0.9886          | 0.6786   | 0.6723 |
| No log        | 11.0  | 77   | 0.8753          | 0.75     | 0.7500 |
| No log        | 12.0  | 84   | 0.9046          | 0.7679   | 0.7657 |
| No log        | 13.0  | 91   | 1.3510          | 0.6786   | 0.6611 |
| No log        | 14.0  | 98   | 1.1851          | 0.75     | 0.7433 |
| No log        | 15.0  | 105  | 1.1149          | 0.7857   | 0.7820 |
| No log        | 16.0  | 112  | 1.3684          | 0.7143   | 0.7063 |
| No log        | 17.0  | 119  | 1.6200          | 0.6964   | 0.6839 |
| No log        | 18.0  | 126  | 1.6112          | 0.6964   | 0.6839 |
| No log        | 19.0  | 133  | 1.4283          | 0.7321   | 0.7270 |
| No log        | 20.0  | 140  | 1.4492          | 0.75     | 0.7445 |
| No log        | 21.0  | 147  | 1.3831          | 0.7321   | 0.7270 |
| No log        | 22.0  | 154  | 1.3764          | 0.7321   | 0.7270 |
| No log        | 23.0  | 161  | 1.3939          | 0.7143   | 0.7063 |
| No log        | 24.0  | 168  | 1.4144          | 0.7143   | 0.7063 |
| No log        | 25.0  | 175  | 1.4170          | 0.7143   | 0.7063 |


### Framework versions

- Transformers 4.29.2
- 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_subtask3", "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\_subtask3
==============================


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: 1.1149
* Accuracy: 0.7857
* F1: 0.7820


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 4.29.2
* 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 4.29.2
* 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 4.29.2
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3