End of training

README.md

@@ -1,6 +1,6 @@
 ---
-license: cc
-base_model: davidmasip/racism
+license: apache-2.0
+base_model: BSC-TeMU/roberta-base-bne
 tags:
 - generated_from_trainer
 metrics:
@@ -8,23 +8,23 @@ metrics:
 - precision
 - recall
 model-index:
-- name: racism-finetuned-detests-wandb24
+- name: roberta-base-bne-finetuned-detests-wandb24
   results: []
 ---
 
 <!-- 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. -->
 
-# racism-finetuned-detests-wandb24
+# roberta-base-bne-finetuned-detests-wandb24
 
-This model is a fine-tuned version of [davidmasip/racism](https://huggingface.co/davidmasip/racism) on the None dataset.
+This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3916
-- Accuracy: 0.8380
-- F1-score: 0.7712
-- Precision: 0.7692
-- Recall: 0.7733
-- Auc: 0.7733
+- Loss: 0.3730
+- Accuracy: 0.8592
+- F1-score: 0.7922
+- Precision: 0.8046
+- Recall: 0.7820
+- Auc: 0.7820
 
 ## Model description
 
@@ -43,9 +43,9 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 3e-05
-- train_batch_size: 64
-- eval_batch_size: 64
+- learning_rate: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -55,8 +55,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc    |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
-| 0.357         | 1.0   | 39   | 0.3343          | 0.8576   | 0.7614   | 0.8374    | 0.7277 | 0.7277 |
-| 0.1109        | 2.0   | 78   | 0.3916          | 0.8380   | 0.7712   | 0.7692    | 0.7733 | 0.7733 |
+| 0.344         | 1.0   | 77   | 0.3268          | 0.8642   | 0.7814   | 0.8347    | 0.7522 | 0.7522 |
+| 0.1996        | 2.0   | 154  | 0.3730          | 0.8592   | 0.7922   | 0.8046    | 0.7820 | 0.7820 |
 
 
 ### Framework versions