End of training

README.md

@@ -1,35 +1,55 @@
 ---
-license: mit
-base_model: distilbert/distilbert-base-uncased
-metrics:
-  - accuracy
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
 model-index:
-  - name: birthday-detector
-    results: []
-datasets:
-  - nroggendorff/doug
-language:
-  - en
-pipeline_tag: text-classification
+- name: birthday-detector
+  results: []
 ---
 
-# Birthday Detector
+<!-- 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. -->
 
-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:
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/noaroggendorff/huggingface/runs/x9vqca8a)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/noaroggendorff/huggingface/runs/x9vqca8a)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/noaroggendorff/huggingface/runs/x9vqca8a)
+# birthday-detector
 
-- Loss: 0.0101
-- Accuracy: 1.0
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
 
-You can easily run it with inference, or run it in python with:
+## Model description
 
-```
-from transformers import pipeline
-classifier = pipeline("sentiment-analysis", model="nroggendorff/birthday-detector")
+More information needed
 
-isBirthday = classifier("happy birthday doug")[0]["label"] == "POSITIVE"
-```
+## Intended uses & limitations
 
-Make sure you have the necessary dependencies installed.
+More information needed
 
-[This models inspiration](https://youtu.be/Q6fjwHPVqjQ)
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 2048
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 32
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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