Training complete

README.md

@@ -1,6 +1,5 @@
 ---
-license: mit
-base_model: xlm-roberta-base
+base_model: xlm_roberta_base_pretrained_wolof_model_pytorch
 tags:
 - generated_from_trainer
 metrics:
@@ -18,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # wolof-finetuned-ner
 
-This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
+This model is a fine-tuned version of [xlm_roberta_base_pretrained_wolof_model_pytorch](https://huggingface.co/xlm_roberta_base_pretrained_wolof_model_pytorch) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0781
-- Precision: 0.8227
-- Recall: 0.8367
-- F1: 0.8297
-- Accuracy: 0.9859
+- Loss: 0.0883
+- Precision: 0.8328
+- Recall: 0.8469
+- F1: 0.8398
+- Accuracy: 0.9864
 
 ## Model description
 
@@ -55,9 +54,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 226  | 0.0955          | 0.7049    | 0.7313 | 0.7179 | 0.9806   |
-| No log        | 2.0   | 452  | 0.0744          | 0.7816    | 0.8401 | 0.8098 | 0.9850   |
-| 0.1416        | 3.0   | 678  | 0.0781          | 0.8227    | 0.8367 | 0.8297 | 0.9859   |
+| No log        | 1.0   | 226  | 0.0731          | 0.7801    | 0.7721 | 0.7761 | 0.9840   |
+| No log        | 2.0   | 452  | 0.0841          | 0.8440    | 0.8095 | 0.8264 | 0.9859   |
+| 0.0825        | 3.0   | 678  | 0.0883          | 0.8328    | 0.8469 | 0.8398 | 0.9864   |
 
 
 ### Framework versions

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4f07f848fd33690d673f02bcdd1c6aa10625f89ee2d8f8d15be6a7feb12a001e
+oid sha256:0baefce3937ecae6db33c4bfc6abf66e3962743a750fe0ffea6dc15b562b4000
 size 1109908201