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username170904/
autotrain-model-datasaur-MjU0NTk3M2U-MDY0YTNiMjE

Name: autotrain-model-datasaur-MjU0NTk3M2U-MDY0YTNiMjE
Availability: InStock

safetensors

bert

generated_from_trainer

token-classification

username170904/datasaur-MjU0NTk3M2U-MDY0YTNiMjE

google-bert/bert-base-uncased

finetune

apache-2.0

model-index

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autotrain-model-datasaur-MjU0NTk3M2U-MDY0YTNiMjE

This model is a fine-tuned version of bert-base-uncased on the username170904/datasaur-MjU0NTk3M2U-MDY0YTNiMjE dataset. It achieves the following results on the evaluation set:

Loss: 0.2033
Precision: 0.0
Recall: 0.0
F1: 0.0
Accuracy: 0.9492

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: 0.0001
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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	2	0.3458	0.9492
No log	2.0	4	0.2644	0.9492
No log	3.0	6	0.2460	0.9492
No log	4.0	8	0.2139	0.9492
No log	5.0	10	0.2033	0.9492

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

username170904/autotrain-model-datasaur-MjU0NTk3M2U-MDY0YTNiMjE

autotrain-model-datasaur-MjU0NTk3M2U-MDY0YTNiMjE

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

username170904/
autotrain-model-datasaur-MjU0NTk3M2U-MDY0YTNiMjE