update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- imdb
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: finetuning-sentiment-model-roberta
+  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: 0.93
+    - name: F1
+      type: f1
+      value: 0.9297658862876254
+    - name: Precision
+      type: precision
+      value: 0.9328859060402684
+    - name: Recall
+      type: recall
+      value: 0.9266666666666666
+---
+
+<!-- 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. -->
+
+# finetuning-sentiment-model-roberta
+
+This model was trained from scratch on the imdb dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2171
+- Accuracy: 0.93
+- F1: 0.9298
+- Precision: 0.9329
+- Recall: 0.9267
+
+## 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: 4
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.144         | 0.98  | 46   | 0.2348          | 0.91     | 0.9132 | 0.8820    | 0.9467 |
+| 0.0957        | 1.98  | 93   | 0.2171          | 0.93     | 0.9298 | 0.9329    | 0.9267 |
+| 0.08          | 2.94  | 138  | 0.2554          | 0.9133   | 0.9167 | 0.8827    | 0.9533 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1
+- Datasets 2.14.4
+- Tokenizers 0.13.3