End of training

README.md

@@ -9,7 +9,7 @@ metrics:
 - accuracy
 - f1
 model-index:
-- name: xlm-roberta-base-finetuned-language-detection
+- name: xlm-roberta-base-finetuned-told-br
   results:
   - task:
       name: Text Classification
@@ -23,22 +23,22 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.7509523809523809
+      value: 0.7457142857142857
     - name: F1
       type: f1
-      value: 0.7517742840944531
+      value: 0.7452494655157376
 ---
 
 <!-- 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-base-finetuned-language-detection
+# xlm-roberta-base-finetuned-told-br
 
 This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the told-br dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4800
-- Accuracy: 0.7510
-- F1: 0.7518
+- Loss: 0.4925
+- Accuracy: 0.7457
+- F1: 0.7452
 
 ## Model description
 
@@ -70,8 +70,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.5911        | 1.0   | 263  | 0.4879          | 0.7514   | 0.7524 |
-| 0.4751        | 2.0   | 526  | 0.4800          | 0.7510   | 0.7518 |
+| 0.5935        | 1.0   | 263  | 0.4970          | 0.7338   | 0.7350 |
+| 0.4797        | 2.0   | 526  | 0.4925          | 0.7457   | 0.7452 |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
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 size 1112205008

runs/Aug09_05-31-03_413957c97aec/events.out.tfevents.1723181470.413957c97aec.2530.0

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+size 6580

training_args.bin

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+size 5176