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# IceBERT-finetuned-ner

This model is a fine-tuned version of [eliasbe/IceBERT-finetuned-ner](https://huggingface.co/eliasbe/IceBERT-finetuned-ner) on the mim_gold_ner dataset.

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Framework versions

- Transformers 4.11.2
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3

{"license": "gpl-3.0", "tags": ["generated_from_trainer"], "datasets": ["mim_gold_ner"], "widget": [{"text": "systurnar gu\u00f0r\u00fan og monique voru einar \u00ed sk\u00f3ginum umkringdar v\u00ed\u00f0i, eik og reyni me\u00f0 \u00fe\u00e1 \u00f3sk a\u00f0 sameinast fj\u00f6lskyldu sinni sem f\u00f3r \u00e1 mai thai og \u00ed b\u00ed\u00f3 parad\u00eds a\u00f0 sj\u00e1 jim carey leika \u00ed the eternal sunshine of the spotless mind.", "results": []}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer dataset:mim_gold_ner license:gpl-3.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #dataset-mim_gold_ner #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us 




# IceBERT-finetuned-ner

This model is a fine-tuned version of eliasbe/IceBERT-finetuned-ner on the mim_gold_ner dataset.

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Framework versions

- Transformers 4.11.2
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3

# IceBERT-finetuned-ner

This model is a fine-tuned version of eliasbe/IceBERT-finetuned-ner on the mim_gold_ner dataset. ## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3 ### Framework versions

- Transformers 4.11.2
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #dataset-mim_gold_ner #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us 
 # IceBERT-finetuned-ner

This model is a fine-tuned version of eliasbe/IceBERT-finetuned-ner on the mim_gold_ner dataset. ## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3 ### Framework versions

- Transformers 4.11.2
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #dataset-mim_gold_ner #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us 
# IceBERT-finetuned-ner

This model is a fine-tuned version of eliasbe/IceBERT-finetuned-ner on the mim_gold_ner dataset.## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3### Framework versions

- Transformers 4.11.2
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3