Model save

README.md

@@ -1,64 +1,66 @@
----
-library_name: transformers
-license: apache-2.0
-base_model: distilbert-base-uncased
-tags:
-- generated_from_trainer
-metrics:
-- accuracy
-model-index:
-- name: empire-content-distilbert
-  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. -->
-
-# empire-content-distilbert
-
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0676
-- Accuracy: 0.9905
-- F1 Macro: 0.9628
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 32
-- seed: 42
-- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: linear
-- num_epochs: 3
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
-| 0.3515        | 1.0   | 113  | 0.1758          | 0.9685   | 0.9382   |
-| 0.0888        | 2.0   | 226  | 0.0826          | 0.9874   | 0.9596   |
-| 0.0513        | 3.0   | 339  | 0.0676          | 0.9905   | 0.9628   |
-
-
-### Framework versions
-
-- Transformers 5.8.1
-- Pytorch 2.11.0+cpu
-- Datasets 4.8.5
-- Tokenizers 0.22.2
+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: empire-content-distilbert
+  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. -->
+
+# empire-content-distilbert
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0786
+- Accuracy: 0.9814
+- F1 Macro: 0.9817
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
+| 0.4091        | 1.0   | 133  | 0.1518          | 0.9654   | 0.9630   |
+| 0.0850        | 2.0   | 266  | 0.0976          | 0.9761   | 0.9757   |
+| 0.0382        | 3.0   | 399  | 0.0757          | 0.9787   | 0.9780   |
+| 0.0209        | 4.0   | 532  | 0.0786          | 0.9814   | 0.9817   |
+| 0.0124        | 5.0   | 665  | 0.0842          | 0.9787   | 0.9790   |
+
+
+### Framework versions
+
+- Transformers 5.9.0
+- Pytorch 2.12.0+cu130
+- Datasets 4.8.5
+- Tokenizers 0.22.2

model.safetensors

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