
<!-- 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-refute-no-label-40-2nd-test-LR10-8-fast-0

This model is a fine-tuned version of [jojoUla/bert-large-cased-sigir-support-refute-no-label-40](https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1394

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.1764        | 1.0   | 1    | 2.3496          |
| 2.7513        | 2.0   | 2    | 0.0370          |
| 2.17          | 3.0   | 3    | 4.6686          |
| 1.8906        | 4.0   | 4    | 1.1284          |
| 1.4806        | 5.0   | 5    | 3.3696          |
| 1.5398        | 6.0   | 6    | 0.4354          |
| 0.8641        | 7.0   | 7    | 0.0010          |
| 2.3655        | 8.0   | 8    | 0.1870          |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-0", "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-refute-no-label-40-2nd-test-LR10-8-fast-0
========================================================================


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


* Loss: 1.1394


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: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8.0


### Training results



### Framework versions


* Transformers 4.30.2
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8.0 ### Training results ### Framework versions


* Transformers 4.30.2
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.13.3
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: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8.0 ### Training results ### Framework versions


* Transformers 4.30.2
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.13.3
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: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8.0### Training results### Framework versions


* Transformers 4.30.2
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.13.3