update model card README.md

README.md

@@ -1,7 +1,7 @@
 ---
 language:
 - mn
-license: bigscience-bloom-rail-1.0
+license: mit
 tags:
 - generated_from_trainer
 metrics:
@@ -19,13 +19,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bloom-NER-fr
 
-This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the None dataset.
+This model is a fine-tuned version of [roberta-large-mnli](https://huggingface.co/roberta-large-mnli) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3194
-- Precision: 0.3970
-- Recall: 0.5804
-- F1: 0.4715
-- Accuracy: 0.9283
+- Loss: 0.2930
+- Precision: 0.5423
+- Recall: 0.6361
+- F1: 0.5854
+- Accuracy: 0.9004
 
 ## Model description
 
@@ -56,12 +56,12 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 1.0627        | 1.0   | 235  | 0.3106          | 0.2650    | 0.4111 | 0.3223 | 0.8957   |
-| 0.3001        | 2.0   | 470  | 0.2626          | 0.3603    | 0.5418 | 0.4328 | 0.9145   |
-| 0.2208        | 3.0   | 705  | 0.2848          | 0.3911    | 0.5569 | 0.4595 | 0.9178   |
-| 0.1573        | 4.0   | 940  | 0.2904          | 0.3479    | 0.5336 | 0.4212 | 0.9149   |
-| 0.1004        | 5.0   | 1175 | 0.2746          | 0.3884    | 0.5704 | 0.4621 | 0.9268   |
-| 0.0594        | 6.0   | 1410 | 0.3194          | 0.3970    | 0.5804 | 0.4715 | 0.9283   |
+| 0.7569        | 1.0   | 47   | 0.4836          | 0.3709    | 0.3924 | 0.3813 | 0.8604   |
+| 0.4348        | 2.0   | 94   | 0.3771          | 0.4395    | 0.5443 | 0.4863 | 0.8687   |
+| 0.3607        | 3.0   | 141  | 0.3232          | 0.5115    | 0.6086 | 0.5559 | 0.8953   |
+| 0.2913        | 4.0   | 188  | 0.2918          | 0.5527    | 0.6255 | 0.5868 | 0.8974   |
+| 0.2602        | 5.0   | 235  | 0.2835          | 0.5485    | 0.6445 | 0.5926 | 0.9028   |
+| 0.2332        | 6.0   | 282  | 0.2930          | 0.5423    | 0.6361 | 0.5854 | 0.9004   |
 
 
 ### Framework versions