Training in progress, epoch 1

README.md

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----
-license: mit
-base_model: distilbert/distilbert-base-uncased
-metrics:
-  - accuracy
-model-index:
-  - name: birthday-detector
-    results: []
-datasets:
-  - nroggendorff/doug
-language:
-  - en
-pipeline_tag: text-classification
----
-
-# Birthday Detector
-
-This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased).
-It achieves the following results on the evaluation set:
-
-- Loss: 0.0101
-- Accuracy: 1.0
-
-You can easily run it with inference, or run it in python with:
-
-```
-from transformers import pipeline
-classifier = pipeline("sentiment-analysis", model="nroggendorff/birthday-detector")
-
-isBirthday = classifier("happy birthday doug")[0]["label"] == "POSITIVE"
-```
-
-Make sure you have the necessary dependencies installed.
-
-[This models inspiration](https://youtu.be/Q6fjwHPVqjQ)
+---
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: birthday-detector
+  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. -->
+
+# birthday-detector
+
+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: 0.1095
+- Accuracy: 0.9796
+
+## 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: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 58   | 0.1248          | 0.9592   |
+| No log        | 2.0   | 116  | 0.1100          | 0.9592   |
+| No log        | 3.0   | 174  | 0.1095          | 0.9796   |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.3.0+cpu
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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