Training completed!

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: 0.8600170502983802
+      value: 0.867219445706497
 ---
 
 <!-- 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: 0.1391
-- F1: 0.8600
+- Loss: 0.1343
+- F1: 0.8672
 
 ## Model description
 
@@ -63,14 +64,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.2598        | 1.0   | 525  | 0.1697          | 0.8177 |
-| 0.1253        | 2.0   | 1050 | 0.1343          | 0.8509 |
-| 0.0812        | 3.0   | 1575 | 0.1391          | 0.8600 |
+| 0.2584        | 1.0   | 525  | 0.1500          | 0.8296 |
+| 0.1253        | 2.0   | 1050 | 0.1360          | 0.8551 |
+| 0.0817        | 3.0   | 1575 | 0.1343          | 0.8672 |
 
 
 ### Framework versions
 
-- Transformers 4.30.2
-- Pytorch 1.12.0
-- Datasets 2.13.1
+- Transformers 4.33.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
 - Tokenizers 0.13.3

config.json

@@ -39,7 +39,7 @@
   "pad_token_id": 1,
   "position_embedding_type": "absolute",
   "torch_dtype": "float32",
-  "transformers_version": "4.30.2",
+  "transformers_version": "4.33.1",
   "type_vocab_size": 1,
   "use_cache": true,
   "vocab_size": 250002

pytorch_model.bin

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tokenizer.json

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training_args.bin

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