update model card README.md

README.md

@@ -0,0 +1,88 @@
+---
+tags:
+- generated_from_trainer
+datasets:
+- toydata
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: xlm-roberta-large-ner-hrl-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: toydata
+      type: toydata
+      args: SDN
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9132452695465905
+    - name: Recall
+      type: recall
+      value: 0.9205854126679462
+    - name: F1
+      type: f1
+      value: 0.9169006511739053
+    - name: Accuracy
+      type: accuracy
+      value: 0.9784804945824268
+---
+
+<!-- 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. -->
+
+# xlm-roberta-large-ner-hrl-finetuned-ner
+
+This model is a fine-tuned version of [Davlan/xlm-roberta-large-ner-hrl](https://huggingface.co/Davlan/xlm-roberta-large-ner-hrl) on the toydata dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0944
+- Precision: 0.9132
+- Recall: 0.9206
+- F1: 0.9169
+- Accuracy: 0.9785
+
+## 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: 16
+- eval_batch_size: 16
+- 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   | 408  | 0.0900          | 0.8508    | 0.9303 | 0.8888 | 0.9719   |
+| 0.1087        | 2.0   | 816  | 0.0827          | 0.9043    | 0.9230 | 0.9136 | 0.9783   |
+| 0.0503        | 3.0   | 1224 | 0.0944          | 0.9132    | 0.9206 | 0.9169 | 0.9785   |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0+cu113
+- Datasets 2.3.2
+- Tokenizers 0.12.1