update model card README.md

README.md

@@ -0,0 +1,67 @@
+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: roberta-finetuned-ner
+  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. -->
+
+# roberta-finetuned-ner
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1322
+- Precision: 0.9772
+- Recall: 0.9782
+- F1: 0.9777
+- Accuracy: 0.9767
+
+## 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: 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 253  | 0.1694          | 0.9636    | 0.9555 | 0.9595 | 0.9617   |
+| 0.4479        | 2.0   | 506  | 0.1374          | 0.9743    | 0.9762 | 0.9752 | 0.9743   |
+| 0.4479        | 3.0   | 759  | 0.1322          | 0.9772    | 0.9782 | 0.9777 | 0.9767   |
+
+
+### Framework versions
+
+- Transformers 4.17.0
+- Pytorch 1.10.0+cu111
+- Datasets 2.0.0
+- Tokenizers 0.11.6