Update README.md

README.md

@@ -1,62 +1,46 @@
----
-library_name: transformers
-base_model: huawei-noah/TinyBERT_General_4L_312D
-tags:
-- generated_from_trainer
-metrics:
-- accuracy
-model-index:
-- name: fine_tuned_spam_model
-  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. -->
-
-# fine_tuned_spam_model
-
-This model is a fine-tuned version of [huawei-noah/TinyBERT_General_4L_312D](https://huggingface.co/huawei-noah/TinyBERT_General_4L_312D) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.6292
-- Accuracy: 0.7664
-
-## 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: 5e-05
-- train_batch_size: 16
-- eval_batch_size: 16
-- 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: 3
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.6875        | 1.0   | 364  | 0.7508          | 0.7226   |
-| 0.5574        | 2.0   | 728  | 0.6804          | 0.7292   |
-| 0.5481        | 3.0   | 1092 | 0.6292          | 0.7664   |
-
-
-### Framework versions
-
-- Transformers 4.49.0
-- Pytorch 2.6.0+cpu
-- Datasets 3.3.2
-- Tokenizers 0.21.1
+---
+library_name: transformers
+base_model: huawei-noah/TinyBERT_General_4L_312D
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: fine_tuned_spam_model
+  results: []
+---
+
+# fine_tuned_spam_model
+
+This model is a fine-tuned version of [huawei-noah/TinyBERT_General_4L_312D](https://huggingface.co/huawei-noah/TinyBERT_General_4L_312D) on a dataset of batch-labeled emails
+and SMS messages that were identified to be spam (Enron, spamassassin, sms-spam, etc.).
+It achieves the following results on the evaluation set:
+- Loss: 0.6292
+- Accuracy: 0.7664
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6875        | 1.0   | 364  | 0.7508          | 0.7226   |
+| 0.5574        | 2.0   | 728  | 0.6804          | 0.7292   |
+| 0.5481        | 3.0   | 1092 | 0.6292          | 0.7664   |
+
+
+### Framework versions
+
+- Transformers 4.49.0
+- Pytorch 2.6.0+cpu
+- Datasets 3.3.2
+- Tokenizers 0.21.1