update model card README.md

README.md

@@ -1,5 +1,6 @@
 ---
 license: mit
+base_model: xlm-roberta-base
 tags:
 - generated_from_trainer
 datasets:
@@ -21,7 +22,7 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: 0.8653353814644136
+      value: 0.8644955590981553
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1339
-- F1: 0.8653
+- Loss: 0.1589
+- F1: 0.8645
 
 ## Model description
 
@@ -52,8 +53,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 24
-- eval_batch_size: 24
+- 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
@@ -63,14 +64,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.2583        | 1.0   | 525  | 0.1596          | 0.8231 |
-| 0.1262        | 2.0   | 1050 | 0.1395          | 0.8468 |
-| 0.0824        | 3.0   | 1575 | 0.1339          | 0.8653 |
+| 0.2621        | 1.0   | 1573 | 0.1627          | 0.8236 |
+| 0.1349        | 2.0   | 3146 | 0.1569          | 0.8474 |
+| 0.0819        | 3.0   | 4719 | 0.1589          | 0.8645 |
 
 
 ### Framework versions
 
-- Transformers 4.30.2
+- Transformers 4.31.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.13.1
 - Tokenizers 0.13.3