update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: albert-base-ours-run-3
+ 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. -->
+
+# albert-base-ours-run-3
+
+This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.4381
+- Accuracy: 0.7
+- Precision: 0.6579
+- Recall: 0.6558
+- F1: 0.6568
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.9876 | 1.0 | 200 | 0.9367 | 0.64 | 0.6707 | 0.5623 | 0.5425 |
+| 0.7553 | 2.0 | 400 | 0.7936 | 0.66 | 0.6269 | 0.6298 | 0.6105 |
+| 0.556 | 3.0 | 600 | 0.9257 | 0.71 | 0.6759 | 0.6504 | 0.6563 |
+| 0.3871 | 4.0 | 800 | 0.9893 | 0.63 | 0.5882 | 0.5985 | 0.5876 |
+| 0.2446 | 5.0 | 1000 | 1.1867 | 0.695 | 0.6582 | 0.6563 | 0.6566 |
+| 0.1502 | 6.0 | 1200 | 1.6108 | 0.71 | 0.6708 | 0.6523 | 0.6585 |
+| 0.1049 | 7.0 | 1400 | 2.4882 | 0.645 | 0.6030 | 0.5597 | 0.5649 |
+| 0.0764 | 8.0 | 1600 | 2.0064 | 0.715 | 0.6798 | 0.6602 | 0.6651 |
+| 0.032 | 9.0 | 1800 | 2.6447 | 0.655 | 0.5913 | 0.5774 | 0.5727 |
+| 0.0177 | 10.0 | 2000 | 2.2460 | 0.675 | 0.6290 | 0.6287 | 0.6287 |
+| 0.0153 | 11.0 | 2200 | 2.3537 | 0.69 | 0.6524 | 0.6407 | 0.6408 |
+| 0.006 | 12.0 | 2400 | 2.4205 | 0.695 | 0.6582 | 0.6448 | 0.6486 |
+| 0.0045 | 13.0 | 2600 | 2.3032 | 0.68 | 0.6394 | 0.6314 | 0.6287 |
+| 0.0038 | 14.0 | 2800 | 2.3506 | 0.685 | 0.6388 | 0.6370 | 0.6367 |
+| 0.0034 | 15.0 | 3000 | 2.3750 | 0.7 | 0.6590 | 0.6558 | 0.6573 |
+| 0.0019 | 16.0 | 3200 | 2.4289 | 0.72 | 0.6819 | 0.6723 | 0.6763 |
+| 0.0016 | 17.0 | 3400 | 2.4470 | 0.725 | 0.6892 | 0.6788 | 0.6830 |
+| 0.0002 | 18.0 | 3600 | 2.4374 | 0.71 | 0.6700 | 0.6626 | 0.6657 |
+| 0.0002 | 19.0 | 3800 | 2.4353 | 0.7 | 0.6579 | 0.6558 | 0.6568 |
+| 0.0002 | 20.0 | 4000 | 2.4381 | 0.7 | 0.6579 | 0.6558 | 0.6568 |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.13.0+cu116
+- Tokenizers 0.13.2