End of training

README.md

@@ -8,18 +8,18 @@ metrics:
 - accuracy
 - f1
 model-index:
-- name: sexism-detector-Spanish-2212e-5001
+- name: sexism-detector-Spanish-8822e-5001
   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. -->
 
-# sexism-detector-Spanish-2212e-5001
+# sexism-detector-Spanish-8822e-5001
 
 This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8560
+- Loss: 0.4773
 - Accuracy: 0.8246
 - F1: 0.7453
 
@@ -41,18 +41,19 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 2
-- eval_batch_size: 2
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 42
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- num_epochs: 1
+- num_epochs: 2
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.7775        | 1.0   | 900  | 0.8560          | 0.8246   | 0.7453 |
+| 0.4827        | 1.0   | 225  | 0.4929          | 0.8246   | 0.7453 |
+| 0.4707        | 2.0   | 450  | 0.4773          | 0.8246   | 0.7453 |
 
 
 ### Framework versions