results_G1 – AI Model by Sushant0809 | AlphaNeural AI

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results_G1

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token-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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results_G1

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

Loss: 0.2389
Treatment: 0.9038
Chronic: 0.9179
Cancer: 0.9009
Allergy: 0.8278
Other: 0.9482
Weighted Avg: 0.9309

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Treatment	Chronic	Cancer	Allergy	Other	Weighted Avg
1.1562	0.2717	100	0.6532	0.6522	0.6504	0.1040	0.0	0.8459	0.7235
0.4683	0.5435	200	0.3505	0.8375	0.8724	0.7987	0.0	0.9169	0.8794
0.329	0.8152	300	0.2931	0.8642	0.8808	0.8561	0.6707	0.9307	0.9030
0.2747	1.0870	400	0.3256	0.8618	0.9007	0.8671	0.7720	0.9269	0.9055
0.2343	1.3587	500	0.2949	0.8779	0.8882	0.8597	0.7990	0.9353	0.9108
0.229	1.6304	600	0.2585	0.8864	0.9017	0.8653	0.8235	0.9385	0.9171
0.1988	1.9022	700	0.2474	0.8793	0.9128	0.8916	0.8265	0.9427	0.9218
0.1591	2.1739	800	0.2588	0.8928	0.9111	0.8853	0.8040	0.9429	0.9235
0.1281	2.4457	900	0.2682	0.8952	0.9121	0.8966	0.815	0.9407	0.9236
0.1298	2.7174	1000	0.2450	0.9015	0.9155	0.8937	0.8152	0.9478	0.9292
0.1053	2.9891	1100	0.2389	0.9038	0.9179	0.9009	0.8278	0.9482	0.9309

Framework versions

Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.19.2
Tokenizers 0.19.1