Training complete

README.md

@@ -1,6 +1,6 @@
 ---
 license: mit
-base_model: vonewman/xlm-roberta-base-finetuned-wolof
+base_model: vonewman/xlm-roberta-large-finetuned-wolof
 tags:
 - generated_from_trainer
 metrics:
@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # wolof-finetuned-ner
 
-This model is a fine-tuned version of [vonewman/xlm-roberta-base-finetuned-wolof](https://huggingface.co/vonewman/xlm-roberta-base-finetuned-wolof) on the None dataset.
+This model is a fine-tuned version of [vonewman/xlm-roberta-large-finetuned-wolof](https://huggingface.co/vonewman/xlm-roberta-large-finetuned-wolof) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2937
-- Precision: 0.8082
-- Recall: 0.8741
-- F1: 0.8399
-- Accuracy: 0.9871
+- Loss: 0.2264
+- Precision: 0.7135
+- Recall: 0.8639
+- F1: 0.7815
+- Accuracy: 0.9831
 
 ## Model description
 
@@ -49,15 +49,13 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 1
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 226  | 0.2625          | 0.7522    | 0.8571 | 0.8013 | 0.9846   |
-| No log        | 2.0   | 452  | 0.3009          | 0.7857    | 0.8605 | 0.8214 | 0.9854   |
-| 0.365         | 3.0   | 678  | 0.2937          | 0.8082    | 0.8741 | 0.8399 | 0.9871   |
+| No log        | 1.0   | 226  | 0.2264          | 0.7135    | 0.8639 | 0.7815 | 0.9831   |
 
 
 ### Framework versions