End of training

README.md

@@ -1,6 +1,6 @@
 ---
-license: apache-2.0
-base_model: bert-base-cased
+license: cc-by-sa-4.0
+base_model: classla/xlm-roberta-base-multilingual-text-genre-classifier
 tags:
 - generated_from_trainer
 metrics:
@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # movie-genre-predictions
 
-This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
+This model is a fine-tuned version of [classla/xlm-roberta-base-multilingual-text-genre-classifier](https://huggingface.co/classla/xlm-roberta-base-multilingual-text-genre-classifier) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.6269
-- Accuracy: 0.4435
+- Loss: 1.8254
+- Accuracy: 0.4039
 
 ## Model description
 
@@ -38,30 +38,37 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 128
-- eval_batch_size: 32
-- seed: 67
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 8
+- num_epochs: 15
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 290  | 1.6650          | 0.4176   |
-| 1.7904        | 2.0   | 580  | 1.6128          | 0.4340   |
-| 1.7904        | 3.0   | 870  | 1.5912          | 0.4438   |
-| 1.5099        | 4.0   | 1160 | 1.6025          | 0.4418   |
-| 1.5099        | 5.0   | 1450 | 1.6094          | 0.4469   |
-| 1.3965        | 6.0   | 1740 | 1.6154          | 0.4447   |
-| 1.3179        | 7.0   | 2030 | 1.6240          | 0.4430   |
-| 1.3179        | 8.0   | 2320 | 1.6269          | 0.4435   |
+| 2.0066        | 1.0   | 580  | 1.7868          | 0.3721   |
+| 1.776         | 2.0   | 1160 | 1.7651          | 0.3909   |
+| 1.686         | 3.0   | 1740 | 1.6970          | 0.4086   |
+| 1.6282        | 4.0   | 2320 | 1.6960          | 0.4098   |
+| 1.5714        | 5.0   | 2900 | 1.6749          | 0.4137   |
+| 1.516         | 6.0   | 3480 | 1.6763          | 0.4142   |
+| 1.4244        | 7.0   | 4060 | 1.7029          | 0.4159   |
+| 1.3822        | 8.0   | 4640 | 1.7114          | 0.4143   |
+| 1.3422        | 9.0   | 5220 | 1.7400          | 0.4131   |
+| 1.3099        | 10.0  | 5800 | 1.7681          | 0.4084   |
+| 1.2757        | 11.0  | 6380 | 1.7830          | 0.4049   |
+| 1.2489        | 12.0  | 6960 | 1.7978          | 0.4050   |
+| 1.2039        | 13.0  | 7540 | 1.8142          | 0.4058   |
+| 1.1839        | 14.0  | 8120 | 1.8243          | 0.4044   |
+| 1.1641        | 15.0  | 8700 | 1.8254          | 0.4039   |
 
 
 ### Framework versions
 
-- Transformers 4.33.3
+- Transformers 4.34.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.5
-- Tokenizers 0.13.3
+- Tokenizers 0.14.1