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# bert-large-cased-sigir-support-no-label-40-sigir-tune2nd-LR100-labelled-30

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: 0.6520

## 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: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.8321        | 1.0   | 2    | 4.3250          |
| 3.383         | 2.0   | 4    | 2.4023          |
| 1.9548        | 3.0   | 6    | 1.2925          |
| 1.4856        | 4.0   | 8    | 1.5152          |
| 0.9588        | 5.0   | 10   | 1.7731          |
| 1.2668        | 6.0   | 12   | 1.3830          |
| 0.8441        | 7.0   | 14   | 1.9760          |
| 1.0173        | 8.0   | 16   | 1.2364          |
| 0.6814        | 9.0   | 18   | 1.1771          |
| 0.9044        | 10.0  | 20   | 1.4721          |
| 0.6889        | 11.0  | 22   | 0.8518          |
| 0.5845        | 12.0  | 24   | 0.6993          |
| 0.4068        | 13.0  | 26   | 1.1771          |
| 0.5957        | 14.0  | 28   | 0.5895          |
| 0.4277        | 15.0  | 30   | 0.5326          |
| 0.3736        | 16.0  | 32   | 1.0893          |
| 0.413         | 17.0  | 34   | 1.3267          |
| 0.5718        | 18.0  | 36   | 1.0331          |
| 0.3892        | 19.0  | 38   | 1.0793          |
| 0.3913        | 20.0  | 40   | 0.8742          |
| 0.4794        | 21.0  | 42   | 1.1264          |
| 0.4626        | 22.0  | 44   | 1.1857          |
| 0.2683        | 23.0  | 46   | 1.5181          |
| 0.3436        | 24.0  | 48   | 1.4419          |
| 0.3793        | 25.0  | 50   | 1.4198          |
| 0.356         | 26.0  | 52   | 1.1776          |
| 0.2189        | 27.0  | 54   | 0.7166          |
| 0.286         | 28.0  | 56   | 0.7601          |
| 0.3681        | 29.0  | 58   | 1.2592          |
| 0.5858        | 30.0  | 60   | 0.6520          |


### Framework versions

- Transformers 4.26.0
- 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-LR100-labelled-30", "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-LR100-labelled-30
==========================================================================


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: 0.6520


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: 30.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.0
* 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: 30.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0
* 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: 30.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0
* 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: 30.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2