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# bert-base-uncased-issues-128

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0420
- Micro f1: 0.6972
- Macro f1: 0.5740

## 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-05
- train_batch_size: 4
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.1542        | 1.0   | 404  | 0.0850          | 0.0      | 0.0      |
| 0.0853        | 2.0   | 808  | 0.0826          | 0.0      | 0.0      |
| 0.0828        | 3.0   | 1212 | 0.0776          | 0.0      | 0.0      |
| 0.0734        | 4.0   | 1616 | 0.0673          | 0.1735   | 0.0294   |
| 0.061         | 5.0   | 2020 | 0.0597          | 0.3500   | 0.0797   |
| 0.049         | 6.0   | 2424 | 0.0556          | 0.4449   | 0.1180   |
| 0.0398        | 7.0   | 2828 | 0.0497          | 0.5027   | 0.1615   |
| 0.0321        | 8.0   | 3232 | 0.0472          | 0.5609   | 0.2498   |
| 0.0261        | 9.0   | 3636 | 0.0481          | 0.5212   | 0.2442   |
| 0.0218        | 10.0  | 4040 | 0.0441          | 0.6238   | 0.3251   |
| 0.0182        | 11.0  | 4444 | 0.0423          | 0.6346   | 0.3880   |
| 0.0154        | 12.0  | 4848 | 0.0412          | 0.6573   | 0.4223   |
| 0.0126        | 13.0  | 5252 | 0.0419          | 0.6586   | 0.4570   |
| 0.0109        | 14.0  | 5656 | 0.0416          | 0.6646   | 0.4813   |
| 0.0092        | 15.0  | 6060 | 0.0401          | 0.6677   | 0.5041   |
| 0.0079        | 16.0  | 6464 | 0.0412          | 0.6859   | 0.5323   |
| 0.0068        | 17.0  | 6868 | 0.0435          | 0.6667   | 0.5372   |
| 0.0059        | 18.0  | 7272 | 0.0452          | 0.6735   | 0.5617   |
| 0.0053        | 19.0  | 7676 | 0.0420          | 0.6735   | 0.5590   |
| 0.0042        | 20.0  | 8080 | 0.0420          | 0.6972   | 0.5740   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.11.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-base-uncased-issues-128", "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 

bert-base-uncased-issues-128
============================


This model is a fine-tuned version of bert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0420
* Micro f1: 0.6972
* Macro f1: 0.5740


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-05
* train\_batch\_size: 4
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 4
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.11.0
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-05
* train\_batch\_size: 4
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.11.0