update model card README.md

README.md

@@ -0,0 +1,66 @@
+---
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: lm-ner-linkedin-skills-recognition
+  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. -->
+
+# lm-ner-linkedin-skills-recognition
+
+This model is a fine-tuned version of [algiraldohe/distilbert-base-uncased-linkedin-domain-adaptation](https://huggingface.co/algiraldohe/distilbert-base-uncased-linkedin-domain-adaptation) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0307
+- Precision: 0.9119
+- Recall: 0.9312
+- F1: 0.9214
+- Accuracy: 0.9912
+
+## 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: 64
+- eval_batch_size: 64
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1301        | 1.0   | 729  | 0.0468          | 0.8786    | 0.8715 | 0.8750 | 0.9863   |
+| 0.0432        | 2.0   | 1458 | 0.0345          | 0.8994    | 0.9219 | 0.9105 | 0.9900   |
+| 0.0332        | 3.0   | 2187 | 0.0307          | 0.9119    | 0.9312 | 0.9214 | 0.9912   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3