
<!-- 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. -->

# bert-large-cased-sigir-support-no-label-40-sigir-tune2nd-LR10-labelled-40

This model is a fine-tuned version of [jojoUla/bert-large-cased-sigir-support-no-label-40](https://huggingface.co/jojoUla/bert-large-cased-sigir-support-no-label-40) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4091

## 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: 4e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.0728        | 1.0   | 1    | 3.3883          |
| 3.6431        | 2.0   | 2    | 4.0303          |
| 3.4087        | 3.0   | 3    | 2.1767          |
| 2.522         | 4.0   | 4    | 2.3348          |
| 1.8187        | 5.0   | 5    | 0.7921          |
| 1.5562        | 6.0   | 6    | 1.6986          |
| 1.505         | 7.0   | 7    | 1.7494          |
| 1.4673        | 8.0   | 8    | 1.5797          |
| 1.22          | 9.0   | 9    | 1.7811          |
| 1.5497        | 10.0  | 10   | 2.0455          |
| 0.8699        | 11.0  | 11   | 2.7731          |
| 1.6008        | 12.0  | 12   | 2.3984          |
| 0.9909        | 13.0  | 13   | 1.7870          |
| 1.4982        | 14.0  | 14   | 1.5336          |
| 0.88          | 15.0  | 15   | 0.5394          |
| 0.5231        | 16.0  | 16   | 0.5391          |
| 1.1294        | 17.0  | 17   | 1.2333          |
| 1.5638        | 18.0  | 18   | 1.4246          |
| 1.5274        | 19.0  | 19   | 0.7396          |
| 1.1525        | 20.0  | 20   | 0.7160          |
| 0.7708        | 21.0  | 21   | 3.9853          |
| 0.6681        | 22.0  | 22   | 1.8747          |
| 0.6073        | 23.0  | 23   | 1.0765          |
| 0.64          | 24.0  | 24   | 0.7888          |
| 1.3657        | 25.0  | 25   | 1.0972          |
| 1.1772        | 26.0  | 26   | 0.6801          |
| 1.6493        | 27.0  | 27   | 0.8378          |
| 0.8971        | 28.0  | 28   | 0.5728          |
| 1.3524        | 29.0  | 29   | 1.7829          |
| 0.7754        | 30.0  | 30   | 1.8142          |
| 1.1628        | 31.0  | 31   | 0.7712          |
| 0.4534        | 32.0  | 32   | 1.3779          |
| 0.6799        | 33.0  | 33   | 1.0512          |
| 1.2813        | 34.0  | 34   | 0.5455          |
| 0.6709        | 35.0  | 35   | 1.8824          |
| 0.4398        | 36.0  | 36   | 2.1419          |
| 0.1491        | 37.0  | 37   | 1.2215          |
| 0.7378        | 38.0  | 38   | 1.7122          |
| 0.657         | 39.0  | 39   | 1.4764          |
| 0.9551        | 40.0  | 40   | 0.5116          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-large-cased-sigir-support-no-label-40-sigir-tune2nd-LR10-labelled-40", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert-large-cased-sigir-support-no-label-40-sigir-tune2nd-LR10-labelled-40
=========================================================================


This model is a fine-tuned version of jojoUla/bert-large-cased-sigir-support-no-label-40 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 2.4091


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: 4e-05
* train\_batch\_size: 30
* eval\_batch\_size: 30
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4e-05
* train\_batch\_size: 30
* eval\_batch\_size: 30
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4e-05
* train\_batch\_size: 30
* eval\_batch\_size: 30
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4e-05
* train\_batch\_size: 30
* eval\_batch\_size: 30
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2