distilbert-base-uncased-song-artist-classifier

README.md

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+---
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+model-index:
+- name: song_artist_classifier
+  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. -->
+
+# song_artist_classifier
+
+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: 1.4491
+- F1: [0.8181818181818182, 0.7777777777777777, 0.7368421052631577, 0.5714285714285715, 0.2, 0.7058823529411764, 0.8000000000000002, 0.5833333333333334, 0.4615384615384615, 0.761904761904762, 0.7, 0.8181818181818182, 0.4, 0.64, 0.6666666666666666, 0.7272727272727272, 0.7826086956521738, 0.7272727272727272, 0.5263157894736842, 0.37499999999999994]
+
+## 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: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1                                                                                                                                                                                                                                                                                                                                                    |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| No log        | 1.0   | 95   | 1.5590          | [0.7368421052631577, 0.7777777777777777, 0.7, 0.6666666666666665, 0.4615384615384615, 0.7, 0.761904761904762, 0.5454545454545454, 0.4285714285714285, 0.7200000000000001, 0.7058823529411764, 0.761904761904762, 0.0, 0.6666666666666666, 0.6428571428571429, 0.7272727272727272, 0.9, 0.761904761904762, 0.6666666666666667, 0.3529411764705882]     |
+| No log        | 2.0   | 190  | 1.4491          | [0.8181818181818182, 0.7777777777777777, 0.7368421052631577, 0.5714285714285715, 0.2, 0.7058823529411764, 0.8000000000000002, 0.5833333333333334, 0.4615384615384615, 0.761904761904762, 0.7, 0.8181818181818182, 0.4, 0.64, 0.6666666666666666, 0.7272727272727272, 0.7826086956521738, 0.7272727272727272, 0.5263157894736842, 0.37499999999999994] |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

runs/Mar18_22-45-54_8904e4dee669/events.out.tfevents.1710801955.8904e4dee669.3457.3

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