update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: sentence-compression-roberta
+  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. -->
+
+# sentence-compression-roberta
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3812
+- Accuracy: 0.8294
+- F1: 0.6764
+- Precision: 0.6233
+- Recall: 0.7394
+
+## 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: 16
+- eval_batch_size: 64
+- seed: 42
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.5358        | 1.0   | 50   | 0.5310          | 0.7666   | 0.1251 | 0.6541    | 0.0691 |
+| 0.4129        | 2.0   | 100  | 0.3988          | 0.8103   | 0.5023 | 0.6838    | 0.3969 |
+| 0.3295        | 3.0   | 150  | 0.3812          | 0.8294   | 0.6764 | 0.6233    | 0.7394 |
+
+
+### Framework versions
+
+- Transformers 4.12.5
+- Pytorch 1.10.0+cu113
+- Datasets 1.16.1
+- Tokenizers 0.10.3