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# exist-2023-task2

This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4756
- F1: 0.7027

## 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: 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 97   | 1.0175          | 0.4991 |
| No log        | 2.0   | 194  | 0.8374          | 0.5695 |
| No log        | 3.0   | 291  | 0.7967          | 0.5876 |
| No log        | 4.0   | 388  | 0.7797          | 0.5982 |
| No log        | 5.0   | 485  | 0.7161          | 0.6424 |
| 0.8645        | 6.0   | 582  | 0.6662          | 0.6302 |
| 0.8645        | 7.0   | 679  | 0.6580          | 0.6385 |
| 0.8645        | 8.0   | 776  | 0.6465          | 0.6491 |
| 0.8645        | 9.0   | 873  | 0.8620          | 0.5650 |
| 0.8645        | 10.0  | 970  | 0.5704          | 0.6852 |
| 0.6764        | 11.0  | 1067 | 0.5434          | 0.6806 |
| 0.6764        | 12.0  | 1164 | 0.7109          | 0.6192 |
| 0.6764        | 13.0  | 1261 | 0.5411          | 0.6708 |
| 0.6764        | 14.0  | 1358 | 0.5557          | 0.6675 |
| 0.6764        | 15.0  | 1455 | 0.5483          | 0.6701 |
| 0.56          | 16.0  | 1552 | 0.5155          | 0.6817 |
| 0.56          | 17.0  | 1649 | 0.5375          | 0.6750 |
| 0.56          | 18.0  | 1746 | 0.4858          | 0.6984 |
| 0.56          | 19.0  | 1843 | 0.4571          | 0.7091 |
| 0.56          | 20.0  | 1940 | 0.4756          | 0.7027 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "exist-2023-task2", "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 

exist-2023-task2
================


This model is a fine-tuned version of microsoft/Multilingual-MiniLM-L12-H384 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4756
* F1: 0.7027


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: 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: 20


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 20 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+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: 2e-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: 20 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3