metadata

license: mit
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: tmvar_2e-05
    results: []

tmvar_2e-05

This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0136
Precision: 0.8308
Recall: 0.8757
F1: 0.8526
Accuracy: 0.9968

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: 2e-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
training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.5077	1.47	25	0.1015	0.0	0.0	0.0	0.9843
0.0834	2.94	50	0.0463	0.3581	0.4162	0.3850	0.9877
0.0348	4.41	75	0.0315	0.3846	0.4324	0.4071	0.9896
0.0285	5.88	100	0.0234	0.5157	0.6216	0.5637	0.9927
0.0149	7.35	125	0.0174	0.7801	0.8054	0.7926	0.9957
0.0104	8.82	150	0.0156	0.78	0.8432	0.8104	0.9959
0.0059	10.29	175	0.0160	0.8360	0.8541	0.8449	0.9960
0.005	11.76	200	0.0139	0.8333	0.8649	0.8488	0.9964
0.003	13.24	225	0.0164	0.8263	0.8486	0.8373	0.9961
0.0024	14.71	250	0.0146	0.7980	0.8541	0.8251	0.9964
0.0023	16.18	275	0.0132	0.8267	0.9027	0.8630	0.9969
0.0016	17.65	300	0.0133	0.8274	0.8811	0.8534	0.9971
0.0015	19.12	325	0.0129	0.8235	0.9081	0.8638	0.9971
0.0014	20.59	350	0.0163	0.8703	0.8703	0.8703	0.9968
0.0013	22.06	375	0.0141	0.8402	0.8811	0.8602	0.9969
0.0013	23.53	400	0.0145	0.8438	0.8757	0.8594	0.9968
0.0011	25.0	425	0.0149	0.8482	0.8757	0.8617	0.9969
0.0011	26.47	450	0.0138	0.8351	0.8757	0.8549	0.9968
0.0011	27.94	475	0.0136	0.8308	0.8757	0.8526	0.9968

Framework versions

Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.2