update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- biocreative_gene_mention
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: gene_finetuned
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: biocreative_gene_mention
+      type: biocreative_gene_mention
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8389085168758926
+    - name: Recall
+      type: recall
+      value: 0.8737864077669902
+    - name: F1
+      type: f1
+      value: 0.8559923298178332
+    - name: Accuracy
+      type: accuracy
+      value: 0.9581707699896856
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# gene_finetuned
+
+This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the biocreative_gene_mention dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1217
+- Precision: 0.8389
+- Recall: 0.8738
+- F1: 0.8560
+- Accuracy: 0.9582
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 157  | 0.1379          | 0.7838    | 0.8403 | 0.8111 | 0.9487   |
+| No log        | 2.0   | 314  | 0.1188          | 0.8394    | 0.8642 | 0.8516 | 0.9570   |
+| No log        | 3.0   | 471  | 0.1217          | 0.8389    | 0.8738 | 0.8560 | 0.9582   |
+
+
+### Framework versions
+
+- Transformers 4.27.4
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.2