update model card README.md

README.md

@@ -0,0 +1,76 @@
+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: Yepes_0.0001_0404_ES6_strict_tok
+  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. -->
+
+# Yepes_0.0001_0404_ES6_strict_tok
+
+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: 0.1677
+- Precision: 0.0
+- Recall: 0.0
+- F1: 0.0
+- Accuracy: 0.9663
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
+| 0.4994        | 0.43  | 25   | 0.2236          | 0.0       | 0.0    | 0.0 | 0.9663   |
+| 0.2637        | 0.86  | 50   | 0.2267          | 0.0       | 0.0    | 0.0 | 0.9663   |
+| 0.2245        | 1.29  | 75   | 0.1961          | 0.0       | 0.0    | 0.0 | 0.9663   |
+| 0.2446        | 1.72  | 100  | 0.1767          | 0.0       | 0.0    | 0.0 | 0.9663   |
+| 0.2184        | 2.16  | 125  | 0.1910          | 0.0       | 0.0    | 0.0 | 0.9663   |
+| 0.203         | 2.59  | 150  | 0.1718          | 0.0       | 0.0    | 0.0 | 0.9663   |
+| 0.2113        | 3.02  | 175  | 0.1710          | 0.0       | 0.0    | 0.0 | 0.9663   |
+| 0.2112        | 3.45  | 200  | 0.1680          | 0.0       | 0.0    | 0.0 | 0.9663   |
+| 0.2123        | 3.88  | 225  | 0.1661          | 0.0       | 0.0    | 0.0 | 0.9663   |
+| 0.2713        | 4.31  | 250  | 0.1657          | 0.0       | 0.0    | 0.0 | 0.9663   |
+| 0.194         | 4.74  | 275  | 0.1716          | 0.0       | 0.0    | 0.0 | 0.9663   |
+| 0.202         | 5.17  | 300  | 0.1677          | 0.0       | 0.0    | 0.0 | 0.9663   |
+
+
+### Framework versions
+
+- Transformers 4.27.4
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.3