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# bert-base-uncased-finetuned-academic

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the elsevier-oa-cc-by dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5893

## 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: 1e-05
- train_batch_size: 40
- eval_batch_size: 40
- seed: 42
- optimizer: Adam with betas=(0.9,0.97) and epsilon=0.0001
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.9591        | 0.25  | 820  | 2.6567          |
| 2.7993        | 0.5   | 1640 | 2.6006          |
| 2.7519        | 0.75  | 2460 | 2.5707          |
| 2.7319        | 1.0   | 3280 | 2.5763          |
| 2.7359        | 1.25  | 4100 | 2.5866          |
| 2.7451        | 1.5   | 4920 | 2.5855          |
| 2.7421        | 1.75  | 5740 | 2.5770          |
| 2.7319        | 2.0   | 6560 | 2.5762          |
| 2.7356        | 2.25  | 7380 | 2.5807          |
| 2.7376        | 2.5   | 8200 | 2.5813          |
| 2.7386        | 2.75  | 9020 | 2.5841          |
| 2.7378        | 3.0   | 9840 | 2.5737          |


### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["elsevier-oa-cc-by"], "model-index": [{"name": "bert-base-uncased-finetuned-academic", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer dataset:elsevier-oa-cc-by license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #dataset-elsevier-oa-cc-by #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert-base-uncased-finetuned-academic
====================================


This model is a fine-tuned version of bert-base-uncased on the elsevier-oa-cc-by dataset.
It achieves the following results on the evaluation set:


* Loss: 2.5893


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: 1e-05
* train\_batch\_size: 40
* eval\_batch\_size: 40
* seed: 42
* optimizer: Adam with betas=(0.9,0.97) and epsilon=0.0001
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 40
* eval\_batch\_size: 40
* seed: 42
* optimizer: Adam with betas=(0.9,0.97) and epsilon=0.0001
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #dataset-elsevier-oa-cc-by #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 40
* eval\_batch\_size: 40
* seed: 42
* optimizer: Adam with betas=(0.9,0.97) and epsilon=0.0001
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #dataset-elsevier-oa-cc-by #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 40
* eval\_batch\_size: 40
* seed: 42
* optimizer: Adam with betas=(0.9,0.97) and epsilon=0.0001
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1