End of training

README.md

@@ -0,0 +1,73 @@
+---
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: distilbert-scam-classifier-v1.1
+  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. -->
+
+# distilbert-scam-classifier-v1.1
+
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0022
+- Accuracy: {'accuracy': 1.0}
+- Precision: {'precision': 1.0}
+- Recall: {'recall': 1.0}
+- F1: {'f1': 1.0}
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy             | Precision                         | Recall             | F1                         |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:---------------------------------:|:------------------:|:--------------------------:|
+| No log        | 1.0   | 40   | 0.0981          | {'accuracy': 0.9875} | {'precision': 0.9878048780487806} | {'recall': 0.9875} | {'f1': 0.9874980465697764} |
+| No log        | 2.0   | 80   | 0.0588          | {'accuracy': 0.9875} | {'precision': 0.9878048780487806} | {'recall': 0.9875} | {'f1': 0.9874980465697764} |
+| No log        | 3.0   | 120  | 0.0035          | {'accuracy': 1.0}    | {'precision': 1.0}                | {'recall': 1.0}    | {'f1': 1.0}                |
+| No log        | 4.0   | 160  | 0.0033          | {'accuracy': 1.0}    | {'precision': 1.0}                | {'recall': 1.0}    | {'f1': 1.0}                |
+| No log        | 5.0   | 200  | 0.0029          | {'accuracy': 1.0}    | {'precision': 1.0}                | {'recall': 1.0}    | {'f1': 1.0}                |
+| No log        | 6.0   | 240  | 0.0028          | {'accuracy': 1.0}    | {'precision': 1.0}                | {'recall': 1.0}    | {'f1': 1.0}                |
+| No log        | 7.0   | 280  | 0.0025          | {'accuracy': 1.0}    | {'precision': 1.0}                | {'recall': 1.0}    | {'f1': 1.0}                |
+| No log        | 8.0   | 320  | 0.0022          | {'accuracy': 1.0}    | {'precision': 1.0}                | {'recall': 1.0}    | {'f1': 1.0}                |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b7ac6bbc3791f024e304c2084a4bd66f3d19a53cd96dc65c6aad9b21d4a105f1
+oid sha256:e5fdc0daeb73db4dfdb6d5d82278322d2036a229094cc9b273b8c955b394c0d7
 size 267832560

runs/May02_16-23-25_fd574d061156/events.out.tfevents.1714667006.fd574d061156.442.7

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:93a92d1d5ce0d48bbd7b48b1de144b071277c475523c0691234b277c4cdf12df
-size 6601
+oid sha256:e218749f259228e15b9f39c117280d571e0362bf9f372459a8db16253ad84ffd
+size 7226