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roberta_finetuned_astronomicalNER – AI Model by mazzaqq | AlphaNeural AI
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roberta_finetuned_astronomicalNER
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transformers
pytorch
tensorboard
xlm-roberta
token-classification
generated_from_trainer
autotrain_compatible
endpoints_compatible
us
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roberta_finetuned_astronomicalNER
This model is a fine-tuned version of
xlm-roberta-large-finetuned-conll03-english
for NER on astronomical objects. The dataset comes from the Shared Task
DEAL: Detecting Entities in the Astrophysics Literature
The model achieves the following results on the evaluation set:
Loss: 0.1416
Precision: 0.7659
Recall: 0.7986
F1: 0.7819
Accuracy: 0.9640
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
176
0.1571
0.7362
0.7788
0.7569
0.9593
No log
2.0
352
0.1416
0.7529
0.7831
0.7677
0.9624
0.1109
3.0
528
0.1416
0.7659
0.7986
0.7819
0.9640
Framework versions
Transformers 4.21.1
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1
