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Mardiyyah/
CeLLaTe-ner-2class-pubmedbert-tapt-combData-tokenizer-adapted-baseline

Name: CeLLaTe-ner-2class-pubmedbert-tapt-combData-tokenizer-adapted-baseline
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CeLLaTe-ner-2class-pubmedbert-tapt-combData-tokenizer-adapted-baseline

This model is a fine-tuned version of Mardiyyah/CeLLaTe-tapt-pubmedbert-tokenizer-adapted-baseline-combinedData on the OTAR3088/CeLLaTe-ner-2class-iob_final dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 3407
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.01
num_epochs: 20
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	Micro F1	Weighted F1	Macro F1	Accuracy
0.2456	1.0	263	0.0655	0.5680	0.6957	0.6254	0.6265	0.6334	0.9776
0.0403	2.0	526	0.0568	0.7239	0.6795	0.7010	0.7009	0.6974	0.9822
0.0256	3.0	789	0.0579	0.7702	0.7234	0.7460	0.7461	0.7503	0.9837
0.0187	4.0	1052	0.0662	0.7530	0.7276	0.7401	0.7406	0.7524	0.9837
0.0143	5.0	1315	0.0653	0.7464	0.7096	0.7275	0.7275	0.7146	0.9833
0.0112	6.0	1578	0.0696	0.7356	0.7126	0.7239	0.7240	0.7135	0.9829
0.0083	7.0	1841	0.0747	0.7359	0.7589	0.7472	0.7476	0.7551	0.9844
0.0065	8.0	2104	0.0829	0.7665	0.7246	0.7450	0.7450	0.7471	0.9839
0.0056	9.0	2367	0.0845	0.7562	0.7462	0.7512	0.7513	0.7574	0.9841
0.0046	10.0	2630	0.0899	0.7752	0.7029	0.7373	0.7373	0.7402	0.9834
0.0039	11.0	2893	0.0848	0.7368	0.7661	0.7512	0.7521	0.7635	0.9839
0.0036	12.0	3156	0.0880	0.7762	0.7384	0.7569	0.7573	0.7663	0.9846
0.0029	13.0	3419	0.0942	0.7506	0.7619	0.7562	0.7564	0.7639	0.9845
0.0025	14.0	3682	0.0936	0.7637	0.7619	0.7628	0.7632	0.7730	0.9846
0.0023	15.0	3945	0.0970	0.7648	0.7625	0.7636	0.7639	0.7724	0.9845
0.0018	16.0	4208	0.0988	0.7717	0.7583	0.7649	0.7654	0.7750	0.9846
0.0017	17.0	4471	0.1000	0.7821	0.7535	0.7675	0.7678	0.7765	0.9845
0.0016	18.0	4734	0.1010	0.7648	0.7589	0.7618	0.7622	0.7713	0.9844
0.0014	19.0	4997	0.1044	0.7752	0.7529	0.7639	0.7642	0.7742	0.9844
0.0014	20.0	5260	0.1044	0.7719	0.7529	0.7623	0.7626	0.7729	0.9843