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# bert-large-cased-sigir-LR10-1-prepend-20

This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8946

## 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: 20.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.8237        | 1.0   | 1    | 2.8391          |
| 3.6537        | 2.0   | 2    | 3.8003          |
| 1.9566        | 3.0   | 3    | 2.6997          |
| 1.0962        | 4.0   | 4    | 2.4019          |
| 2.7754        | 5.0   | 5    | 1.0750          |
| 2.2666        | 6.0   | 6    | 3.7118          |
| 1.33          | 7.0   | 7    | 2.3186          |
| 2.1846        | 8.0   | 8    | 2.0246          |
| 2.5284        | 9.0   | 9    | 2.0090          |
| 1.9864        | 10.0  | 10   | 3.3644          |
| 1.8111        | 11.0  | 11   | 2.5410          |
| 1.6821        | 12.0  | 12   | 1.2586          |
| 1.491         | 13.0  | 13   | 1.4496          |
| 1.9611        | 14.0  | 14   | 1.7305          |
| 1.4182        | 15.0  | 15   | 1.7722          |
| 2.0556        | 16.0  | 16   | 1.2964          |
| 0.9024        | 17.0  | 17   | 2.0762          |
| 1.5746        | 18.0  | 18   | 2.7421          |
| 1.2275        | 19.0  | 19   | 2.1911          |
| 1.6938        | 20.0  | 20   | 3.0756          |


### 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-LR10-1-prepend-20", "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-LR10-1-prepend-20
========================================


This model is a fine-tuned version of bert-large-cased on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.8946


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: 20.0
* 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: 20.0
* 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: 20.0
* 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: 20.0
* 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