End of training

README.md

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+---
+license: mit
+base_model: roberta-large
+tags:
+- generated_from_trainer
+datasets:
+- cosmos_qa
+metrics:
+- accuracy
+model-index:
+- name: roberta-large-finetuned-cosmos
+  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. -->
+
+# roberta-large-finetuned-cosmos
+
+This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the cosmos_qa dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3863
+- Accuracy: 0.2533
+
+## 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: 2
+- eval_batch_size: 2
+- 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 1.39          | 1.0   | 12631 | 1.3863          | 0.2586   |
+| 1.3956        | 2.0   | 25262 | 1.3863          | 0.2563   |
+| 1.3902        | 3.0   | 37893 | 1.3863          | 0.2533   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.1.1+cu121
+- Datasets 2.12.0
+- Tokenizers 0.13.2

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