update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: deberta-v3-large__sst2__train-8-1
+  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. -->
+
+# deberta-v3-large__sst2__train-8-1
+
+This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7020
+- Accuracy: 0.5008
+
+## 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: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 50
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6773        | 1.0   | 3    | 0.7822          | 0.25     |
+| 0.6587        | 2.0   | 6    | 0.8033          | 0.25     |
+| 0.693         | 3.0   | 9    | 0.8101          | 0.25     |
+| 0.5979        | 4.0   | 12   | 1.1235          | 0.25     |
+| 0.4095        | 5.0   | 15   | 1.3563          | 0.25     |
+| 0.2836        | 6.0   | 18   | 1.5325          | 0.5      |
+| 0.1627        | 7.0   | 21   | 1.7786          | 0.25     |
+| 0.0956        | 8.0   | 24   | 2.0067          | 0.5      |
+| 0.0535        | 9.0   | 27   | 2.3351          | 0.5      |
+| 0.0315        | 10.0  | 30   | 2.6204          | 0.5      |
+| 0.0182        | 11.0  | 33   | 2.8483          | 0.5      |
+
+
+### Framework versions
+
+- Transformers 4.15.0
+- Pytorch 1.10.2+cu102
+- Datasets 1.18.2
+- Tokenizers 0.10.3