update model card README.md

README.md

@@ -1,10 +1,98 @@
 ---
+license: mit
+tags:
+- generated_from_trainer
 datasets:
-- >-
-  autoevaluate/autoeval-eval-chintagunta85__ncbi_disease-ncbi_disease-f4d843-3192989823
+- ncbi_disease
 metrics:
-- accuracy
-- f1
 - precision
 - recall
----
+- f1
+- accuracy
+model-index:
+- name: MLMA_lab9
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: ncbi_disease
+      type: ncbi_disease
+      config: ncbi_disease
+      split: validation
+      args: ncbi_disease
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.12389380530973451
+    - name: Recall
+      type: recall
+      value: 0.017789072426937738
+    - name: F1
+      type: f1
+      value: 0.031111111111111107
+    - name: Accuracy
+      type: accuracy
+      value: 0.9177455063979887
+---
+
+<!-- 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. -->
+
+# MLMA_lab9
+
+This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the ncbi_disease dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3328
+- Precision: 0.1239
+- Recall: 0.0178
+- F1: 0.0311
+- Accuracy: 0.9177
+
+## 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: 0.0001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2903        | 1.0   | 680  | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
+| 0.2907        | 2.0   | 1360 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
+| 0.2885        | 3.0   | 2040 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
+| 0.2861        | 4.0   | 2720 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
+| 0.2948        | 5.0   | 3400 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
+| 0.2881        | 6.0   | 4080 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
+| 0.292         | 7.0   | 4760 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
+| 0.2882        | 8.0   | 5440 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
+| 0.2905        | 9.0   | 6120 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
+| 0.2881        | 10.0  | 6800 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.3