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jclondonol/
nasa-astrophysics-ner-final

Name: nasa-astrophysics-ner-final
Availability: InStock

generated_from_trainer

distilbert/distilbert-base-uncased

finetune

apache-2.0

endpoints_compatible

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nasa-astrophysics-ner-final

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1678
Precision: 0.7445
Recall: 0.7837
F1: 0.7636
Accuracy: 0.9622

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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.3650	1.0	110	0.2811	0.5968	0.5778	0.5872	0.9351
0.2105	2.0	220	0.1911	0.6661	0.7025	0.6838	0.9526
0.1406	3.0	330	0.1708	0.6800	0.7524	0.7144	0.9552
0.1136	4.0	440	0.1566	0.7266	0.7687	0.7471	0.9605
0.0812	5.0	550	0.1604	0.7334	0.7701	0.7513	0.9608
0.0669	6.0	660	0.1618	0.7437	0.7715	0.7573	0.9615
0.0620	7.0	770	0.1612	0.7311	0.7840	0.7566	0.9613
0.0505	8.0	880	0.1638	0.7431	0.7860	0.7640	0.9619
0.0443	9.0	990	0.1670	0.7438	0.7867	0.7646	0.9623
0.0439	10.0	1100	0.1678	0.7445	0.7837	0.7636	0.9622

Framework versions

Transformers 5.8.1
Pytorch 2.12.0+cu130
Datasets 4.8.5
Tokenizers 0.22.2

jclondonol/nasa-astrophysics-ner-final

nasa-astrophysics-ner-final

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jclondonol/
nasa-astrophysics-ner-final