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product-review-information-density-detection-distilbert

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distilbert

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aloychow commited on Apr 18, 2024

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 ---
-language:
-- en
 metrics:
 - accuracy
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
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-## Model Details
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 ---
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
 metrics:
 - accuracy
+model-index:
+- name: product-review-information-density-detection-distilbert
+  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. -->
+# product-review-information-density-detection-distilbert
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2972
+- Accuracy: 0.8387
+## 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: 48
+- eval_batch_size: 48
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 50
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 67   | 0.5551          | 0.7438   |
+| No log        | 2.0   | 134  | 0.4422          | 0.8163   |
+| No log        | 3.0   | 201  | 0.4285          | 0.84     |
+| No log        | 4.0   | 268  | 0.4707          | 0.8263   |
+| No log        | 5.0   | 335  | 0.5597          | 0.825    |
+| No log        | 6.0   | 402  | 0.6377          | 0.8387   |
+| No log        | 7.0   | 469  | 0.7444          | 0.8363   |
+| 0.2608        | 8.0   | 536  | 0.7492          | 0.8413   |
+| 0.2608        | 9.0   | 603  | 0.7549          | 0.8387   |
+| 0.2608        | 10.0  | 670  | 0.8264          | 0.845    |
+| 0.2608        | 11.0  | 737  | 1.0370          | 0.8187   |
+| 0.2608        | 12.0  | 804  | 0.9359          | 0.8313   |
+| 0.2608        | 13.0  | 871  | 0.9810          | 0.8387   |
+| 0.2608        | 14.0  | 938  | 1.0293          | 0.84     |
+| 0.0251        | 15.0  | 1005 | 1.0647          | 0.8263   |
+| 0.0251        | 16.0  | 1072 | 1.0693          | 0.83     |
+| 0.0251        | 17.0  | 1139 | 1.0656          | 0.8425   |
+| 0.0251        | 18.0  | 1206 | 1.1193          | 0.8313   |
+| 0.0251        | 19.0  | 1273 | 1.1583          | 0.8187   |
+| 0.0251        | 20.0  | 1340 | 1.1257          | 0.8387   |
+| 0.0251        | 21.0  | 1407 | 1.1632          | 0.825    |
+| 0.0251        | 22.0  | 1474 | 1.2419          | 0.8213   |
+| 0.0108        | 23.0  | 1541 | 1.1635          | 0.84     |
+| 0.0108        | 24.0  | 1608 | 1.1951          | 0.8287   |
+| 0.0108        | 25.0  | 1675 | 1.1710          | 0.845    |
+| 0.0108        | 26.0  | 1742 | 1.2204          | 0.83     |
+| 0.0108        | 27.0  | 1809 | 1.2166          | 0.8413   |
+| 0.0108        | 28.0  | 1876 | 1.2335          | 0.8363   |
+| 0.0108        | 29.0  | 1943 | 1.2355          | 0.8363   |
+| 0.007         | 30.0  | 2010 | 1.2423          | 0.8425   |
+| 0.007         | 31.0  | 2077 | 1.2511          | 0.8425   |
+| 0.007         | 32.0  | 2144 | 1.2563          | 0.84     |
+| 0.007         | 33.0  | 2211 | 1.2501          | 0.8413   |
+| 0.007         | 34.0  | 2278 | 1.2431          | 0.8375   |
+| 0.007         | 35.0  | 2345 | 1.2553          | 0.8387   |
+| 0.007         | 36.0  | 2412 | 1.2635          | 0.8425   |
+| 0.007         | 37.0  | 2479 | 1.2970          | 0.835    |
+| 0.0061        | 38.0  | 2546 | 1.2894          | 0.8375   |
+| 0.0061        | 39.0  | 2613 | 1.2773          | 0.84     |
+| 0.0061        | 40.0  | 2680 | 1.2836          | 0.84     |
+| 0.0061        | 41.0  | 2747 | 1.2916          | 0.8375   |
+| 0.0061        | 42.0  | 2814 | 1.2869          | 0.8387   |
+| 0.0061        | 43.0  | 2881 | 1.3032          | 0.8287   |
+| 0.0061        | 44.0  | 2948 | 1.3056          | 0.8413   |
+| 0.0047        | 45.0  | 3015 | 1.2813          | 0.8438   |
+| 0.0047        | 46.0  | 3082 | 1.2811          | 0.8413   |
+| 0.0047        | 47.0  | 3149 | 1.2858          | 0.8413   |
+| 0.0047        | 48.0  | 3216 | 1.2960          | 0.8387   |
+| 0.0047        | 49.0  | 3283 | 1.2971          | 0.8387   |
+| 0.0047        | 50.0  | 3350 | 1.2972          | 0.8387   |
+### Framework versions
+- Transformers 4.39.1
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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