update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- sst2
+metrics:
+- accuracy
+model-index:
+- name: sentiment-model-saagie
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: sst2
+      type: sst2
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.785
+---
+
+<!-- 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-model-saagie
+
+This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the sst2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5410
+- Accuracy: 0.785
+
+## 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: 5e-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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5195        | 1.0   | 1500 | 0.4747          | 0.7767   |
+| 0.3794        | 2.0   | 3000 | 0.5344          | 0.79     |
+| 0.3351        | 3.0   | 4500 | 0.5410          | 0.785    |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.8.1
+- Datasets 2.12.0
+- Tokenizers 0.12.1