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# bert-large-cased-sigir-support-no-label-40

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: 1.1107

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.7638        | 1.0   | 246  | 2.2805          |
| 2.1924        | 2.0   | 492  | 1.9602          |
| 1.8921        | 3.0   | 738  | 1.7992          |
| 1.7412        | 4.0   | 984  | 1.7229          |
| 1.6311        | 5.0   | 1230 | 1.6165          |
| 1.5421        | 6.0   | 1476 | 1.5400          |
| 1.4619        | 7.0   | 1722 | 1.5001          |
| 1.3846        | 8.0   | 1968 | 1.4381          |
| 1.3414        | 9.0   | 2214 | 1.4285          |
| 1.2894        | 10.0  | 2460 | 1.4108          |
| 1.2467        | 11.0  | 2706 | 1.3460          |
| 1.1992        | 12.0  | 2952 | 1.3434          |
| 1.1612        | 13.0  | 3198 | 1.2951          |
| 1.1266        | 14.0  | 3444 | 1.2518          |
| 1.0933        | 15.0  | 3690 | 1.2825          |
| 1.0625        | 16.0  | 3936 | 1.2523          |
| 1.0386        | 17.0  | 4182 | 1.2251          |
| 1.0066        | 18.0  | 4428 | 1.2339          |
| 0.9755        | 19.0  | 4674 | 1.1887          |
| 0.9656        | 20.0  | 4920 | 1.2288          |
| 0.9517        | 21.0  | 5166 | 1.1391          |
| 0.9207        | 22.0  | 5412 | 1.1718          |
| 0.8964        | 23.0  | 5658 | 1.1850          |
| 0.8891        | 24.0  | 5904 | 1.1306          |
| 0.8564        | 25.0  | 6150 | 1.1956          |
| 0.851         | 26.0  | 6396 | 1.1263          |
| 0.8331        | 27.0  | 6642 | 1.1060          |
| 0.8143        | 28.0  | 6888 | 1.0689          |
| 0.7972        | 29.0  | 7134 | 1.0772          |
| 0.7857        | 30.0  | 7380 | 1.1103          |
| 0.7687        | 31.0  | 7626 | 1.1635          |
| 0.7653        | 32.0  | 7872 | 1.0736          |
| 0.777         | 33.0  | 8118 | 1.1103          |
| 0.741         | 34.0  | 8364 | 1.0830          |
| 0.7408        | 35.0  | 8610 | 1.0809          |
| 0.736         | 36.0  | 8856 | 1.0894          |
| 0.7362        | 37.0  | 9102 | 1.0691          |
| 0.727         | 38.0  | 9348 | 1.0519          |
| 0.715         | 39.0  | 9594 | 1.0919          |
| 0.7286        | 40.0  | 9840 | 1.1107          |


### 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", "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
==========================================


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: 1.1107


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 4.26.0
* 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: 40.0
* 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: 40.0
* 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: 40.0
* 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