update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: tmvar_0.0001_0404_ES6_strict_tok1
+  results: []
+---
+
+<!-- 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. -->
+
+# tmvar_0.0001_0404_ES6_strict_tok1
+
+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 None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1472
+- Precision: 0.0
+- Recall: 0.0
+- F1: 0.0
+- Accuracy: 0.9561
+
+## 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: 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: 2000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
+| 0.3183        | 0.49  | 25   | 0.2344          | 0.0       | 0.0    | 0.0 | 0.9555   |
+| 0.232         | 0.98  | 50   | 0.2467          | 0.0       | 0.0    | 0.0 | 0.9555   |
+| 0.2357        | 1.47  | 75   | 0.2341          | 0.0       | 0.0    | 0.0 | 0.9555   |
+| 0.2245        | 1.96  | 100  | 0.2373          | 0.0       | 0.0    | 0.0 | 0.9555   |
+| 0.1778        | 2.45  | 125  | 0.1339          | 0.0       | 0.0    | 0.0 | 0.9555   |
+| 0.137         | 2.94  | 150  | 0.1222          | 0.0       | 0.0    | 0.0 | 0.9582   |
+| 0.1146        | 3.43  | 175  | 0.1339          | 0.0       | 0.0    | 0.0 | 0.9625   |
+| 0.1215        | 3.92  | 200  | 0.1472          | 0.0       | 0.0    | 0.0 | 0.9561   |
+
+
+### Framework versions
+
+- Transformers 4.27.4
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.3