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albert_model

Text Classification
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PyTorch
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albert
Generated from Trainer
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update model card README.md

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@@ -4,6 +4,8 @@ tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
 
 
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  model-index:
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  - name: albert_model
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  results: []
@@ -16,8 +18,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8674
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- - Accuracy: 0.9010
 
 
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  ## Model description
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@@ -37,8 +41,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 1e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 334 | 0.3206 | 0.8666 |
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- | 0.4327 | 2.0 | 668 | 0.4502 | 0.8906 |
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- | 0.3178 | 3.0 | 1002 | 0.4517 | 0.8951 |
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- | 0.3178 | 4.0 | 1336 | 0.5688 | 0.9025 |
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- | 0.1649 | 5.0 | 1670 | 0.6359 | 0.8996 |
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- | 0.0707 | 6.0 | 2004 | 0.7573 | 0.8906 |
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- | 0.0707 | 7.0 | 2338 | 0.8200 | 0.8906 |
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- | 0.0216 | 8.0 | 2672 | 0.7581 | 0.9010 |
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- | 0.0168 | 9.0 | 3006 | 0.7530 | 0.9130 |
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- | 0.0168 | 10.0 | 3340 | 0.8194 | 0.9055 |
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- | 0.0075 | 11.0 | 3674 | 0.8633 | 0.9010 |
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- | 0.0037 | 12.0 | 4008 | 0.8079 | 0.9145 |
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- | 0.0037 | 13.0 | 4342 | 0.8283 | 0.9115 |
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- | 0.0018 | 14.0 | 4676 | 0.8508 | 0.9055 |
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- | 0.0003 | 15.0 | 5010 | 0.8674 | 0.9010 |
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  ### Framework versions
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
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+ - f1
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+ - recall
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  model-index:
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  - name: albert_model
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  results: []
 
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  This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6560
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+ - Accuracy: 0.9070
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+ - F1: 0.8852
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+ - Recall: 0.9122
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 1e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
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+ | No log | 1.0 | 167 | 0.3571 | 0.8351 | 0.8142 | 0.9198 |
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+ | No log | 2.0 | 334 | 0.2670 | 0.8891 | 0.8683 | 0.9313 |
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+ | 0.3358 | 3.0 | 501 | 0.2643 | 0.9115 | 0.8885 | 0.8969 |
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+ | 0.3358 | 4.0 | 668 | 0.3804 | 0.9130 | 0.8910 | 0.9046 |
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+ | 0.3358 | 5.0 | 835 | 0.4376 | 0.9070 | 0.8848 | 0.9084 |
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+ | 0.1007 | 6.0 | 1002 | 0.4957 | 0.9100 | 0.8859 | 0.8893 |
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+ | 0.1007 | 7.0 | 1169 | 0.6375 | 0.8801 | 0.8601 | 0.9389 |
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+ | 0.1007 | 8.0 | 1336 | 0.5978 | 0.8996 | 0.8780 | 0.9198 |
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+ | 0.012 | 9.0 | 1503 | 0.6101 | 0.9025 | 0.8816 | 0.9237 |
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+ | 0.012 | 10.0 | 1670 | 0.6209 | 0.9085 | 0.8847 | 0.8931 |
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+ | 0.012 | 11.0 | 1837 | 0.6485 | 0.9010 | 0.8787 | 0.9122 |
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+ | 0.0007 | 12.0 | 2004 | 0.6480 | 0.9070 | 0.8852 | 0.9122 |
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+ | 0.0007 | 13.0 | 2171 | 0.6527 | 0.9055 | 0.8835 | 0.9122 |
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+ | 0.0007 | 14.0 | 2338 | 0.6557 | 0.9055 | 0.8835 | 0.9122 |
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+ | 0.0002 | 15.0 | 2505 | 0.6560 | 0.9070 | 0.8852 | 0.9122 |
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  ### Framework versions