update model card README.md

README.md

@@ -1,17 +1,9 @@
 ---
 license: apache-2.0
 tags:
-- biology
-- science
-- medical
-- biomedical
-- biocuration
-- sourcedata
+- generated_from_trainer
 datasets:
 - source_data_nlp
-widget:
-- text: "XPT of siRNA treated [MASK] cells after 48 hours of knockdown. Treated cells were fed with the indicated amounts of C8L peptid conjugated to iron oxide beads via a disulfide bond. The cells were then exposed to RF33. 70-Luc Reporter [MASK] T cells overnight. Error bars show SD of >3 replicate wells. * p<0.05 for siRNA vs control [MASK] using two-way ANOVA. Representative plot of 3 independent experiments."
-- text: "The [MASK] intensity along the line across a lipid droplet in (A) was measured by ImageJ.The lipid droplet localization of [MASK]-[MASK], represented by two peaks, is clearly visible in fat cells from ppl > [MASK] larvae , but it is lost in fat cells from ppl > [MASK] larvae with [MASK] RNAi or overexpression of [MASK]/[MASK]. More than 30 lipid droplets of each genotype were measured. One typical image curve is shown for each genotype."
 metrics:
 - precision
 - recall
@@ -29,16 +21,13 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9218777784363701
+      value: 0.9227577212638568
     - name: Recall
       type: recall
-      value: 0.9280386657915151
+      value: 0.9288143683990692
     - name: F1
       type: f1
-      value: 0.9249479631281595
-language:
-- en
-pipeline_tag: token-classification
+      value: 0.9257761389318425
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -48,11 +37,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-large](https://huggingface.co/michiyasunaga/BioLinkBERT-large) on the source_data_nlp dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0141
+- Loss: 0.0136
 - Accuracy Score: 0.9950
-- Precision: 0.9219
-- Recall: 0.9280
-- F1: 0.9249
+- Precision: 0.9228
+- Recall: 0.9288
+- F1: 0.9258
 
 ## Model description
 
@@ -83,7 +72,7 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:|
-| 0.0129        | 1.0   | 1569 | 0.0141          | 0.9950         | 0.9219    | 0.9280 | 0.9249 |
+| 0.014         | 1.0   | 1569 | 0.0136          | 0.9950         | 0.9228    | 0.9288 | 0.9258 |
 
 
 ### Framework versions
@@ -91,4 +80,4 @@ The following hyperparameters were used during training:
 - Transformers 4.20.0
 - Pytorch 1.11.0a0+bfe5ad2
 - Datasets 1.17.0
-- Tokenizers 0.12.1
+- Tokenizers 0.12.1