update model card README.md

sentiment_analysis_imbd/README.md

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+---
+license: apache-2.0
+tags:
+- simplification
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+model-index:
+- name: sentiment_analysis_imbd
+  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. -->
+
+# sentiment_analysis_imbd
+
+This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1674
+- Precision: 0.9468
+- Recall: 0.9467
+- F1: 0.9467
+
+## 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
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
+| 0.1819        | 1.0   | 2188 | 0.1674          | 0.9468    | 0.9467 | 0.9467 |
+
+
+### Framework versions
+
+- Transformers 4.27.2
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.1
+- Tokenizers 0.13.2