Training complete

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.969802244788883
+      value: 0.9574581228396704
     - name: Recall
       type: recall
-      value: 0.9789587267332075
+      value: 0.9664519592055824
     - name: F1
       type: f1
-      value: 0.9743589743589745
+      value: 0.9619340189662082
     - name: Accuracy
       type: accuracy
-      value: 0.9894519740718916
+      value: 0.9889216263995286
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the wikiann dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0686
-- Precision: 0.9698
-- Recall: 0.9790
-- F1: 0.9744
-- Accuracy: 0.9895
+- Loss: 0.0495
+- Precision: 0.9575
+- Recall: 0.9665
+- F1: 0.9619
+- Accuracy: 0.9889
 
 ## Model description
 
@@ -67,7 +67,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 1e-05
 - train_batch_size: 4
 - eval_batch_size: 8
 - seed: 42
@@ -81,9 +81,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 427  | 0.0717          | 0.9367    | 0.9701 | 0.9531 | 0.9862   |
-| 0.0221        | 2.0   | 855  | 0.0715          | 0.9560    | 0.9733 | 0.9646 | 0.9880   |
-| 0.0113        | 3.0   | 1281 | 0.0686          | 0.9698    | 0.9790 | 0.9744 | 0.9895   |
+| No log        | 1.0   | 427  | 0.0560          | 0.9339    | 0.9514 | 0.9426 | 0.9828   |
+| 0.1405        | 2.0   | 855  | 0.0539          | 0.9430    | 0.9595 | 0.9512 | 0.9859   |
+| 0.0449        | 3.0   | 1281 | 0.0495          | 0.9575    | 0.9665 | 0.9619 | 0.9889   |
 
 
 ### Framework versions

model.safetensors

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runs/Nov13_04-32-21_server-cvis/events.out.tfevents.1699849957.server-cvis.535932.0

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tokenizer.json

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training_args.bin

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