Model save

README.md

@@ -1,7 +1,7 @@
 ---
 library_name: transformers
-license: mit
-base_model: FacebookAI/roberta-base
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
 tags:
 - generated_from_trainer
 metrics:
@@ -16,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # EMOTION-AI
 
-This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.7185
-- Accuracy: 0.2953
+- Loss: 1.4188
+- Accuracy: 0.5669
 
 ## Model description
 
@@ -38,13 +38,13 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0003
+- learning_rate: 0.0002
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
 - gradient_accumulation_steps: 4
 - total_train_batch_size: 128
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- 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: 2
 
@@ -52,13 +52,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| No log        | 0.9982 | 271  | 2.7301          | 0.2953   |
-| 2.7229        | 1.9963 | 542  | 2.7185          | 0.2953   |
+| No log        | 1.0    | 272  | 1.4966          | 0.5462   |
+| 6.0068        | 1.9945 | 542  | 1.4188          | 0.5669   |
 
 
 ### Framework versions
 
-- Transformers 4.44.2
+- Transformers 4.48.0.dev0
 - Pytorch 2.4.1+cu121
 - Datasets 3.2.0
-- Tokenizers 0.19.1
+- Tokenizers 0.21.0