update model card README.md

README.md

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+---
+license: openrail
+base_model: versae/gzip-bert
+tags:
+- generated_from_trainer
+datasets:
+- imdb
+metrics:
+- accuracy
+model-index:
+- name: gzipbert_imdb_rpe_250k
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: imdb
+      type: imdb
+      config: plain_text
+      split: test
+      args: plain_text
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.50952
+---
+
+<!-- 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. -->
+
+# gzipbert_imdb_rpe_250k
+
+This model is a fine-tuned version of [versae/gzip-bert](https://huggingface.co/versae/gzip-bert) on the imdb dataset.
+It achieves the following results on the evaluation set:
+- Loss: 6.0866
+- Accuracy: 0.5095
+
+## 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-06
+- 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.003         | 1.0   | 1563 | 5.1727          | 0.5548   |
+| 0.0061        | 2.0   | 3126 | 5.7975          | 0.5176   |
+| 0.0056        | 3.0   | 4689 | 5.6762          | 0.5107   |
+| 0.0019        | 4.0   | 6252 | 6.0355          | 0.5082   |
+| 0.0043        | 5.0   | 7815 | 6.0866          | 0.5095   |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.0
+- Tokenizers 0.13.3